LEAD DATA ENGINEER COVER LETTER TEMPLATE

• Develop and maintain enterprise data warehouse and business intelligence solutions
• Design, build, and test solutions for data transformation from a variety of data sources while modeling data in an efficient and performant manner
• Work directly with customers to understand reporting and analytics needs
• Collaborate with customers and BI analysts to design and build BI semantic solutions to enable governed self-service
• Assist in building a technical roadmap for analytic products
• Provide technical and professional mentorship to teammates
• Work with Product Owners and Scrum Masters to help determine priority and assess timelines
• Participate in all agile ceremonies, including planning, pointing, demos, and retros

Skills: Enterprise Data Warehousing, Data Transformation, BI Solutions, Semantic Modeling, Customer Collaboration, Technical Mentorship, Agile Delivery, Product Roadmapping

• Enforce industry and company best practices within the team
• Prioritize unit tests, both manual and automated, to ensure the highest code quality
• Responsible for timely and thorough code reviews
• Responsible for documenting all solutions and metadata to the required company standard
• Continually learn and stay up-to-date with the ever-changing analytics technical landscape
• Mentor other team members on new technologies and practices
• Work with external vendors to ensure deliverables meet company needs and standards
• Own the data ops delivery pipeline and processes
• Participate in architectural design decisions and communicate those to the team

Skills: Best Practices Enforcement, Unit Testing, Code Reviews, Technical Documentation, Continuous Learning, Team Mentoring, Vendor Management, DataOps Delivery

• Plan with analysts and data scientists regularly to translate requirements into solutions and ensure delivery of successful business outcomes
• Architect the data warehouse and data lake for the cloud
• Ensure environments are stable and available
• Lead a team using Agile Kanban workflows to safely code, review, test and deploy solutions, using source control to manage changes
• Manage the DevOps processes for Data, and any tooling that guides the processes
• Design and build with the on-premise Microsoft BI stack, including SSIS, SQL Server and Power BI
• Design and build with an AWS-based BI stack, including Lambda, Redshift and Matillion
• Design and build connections to APIs, flat files, databases and data streams to the data lake (ELT)
• Shape data from the data lake and form it into a Kimball data warehouse (ETL)
• Build containers for data model endpoints
• Design appropriate data quality, integrity and alerting in all solutions, and ensure they are maintained

Skills: Data Warehouse Architecture, Cloud Data Lakes, Agile Kanban Leadership, Data DevOps, Microsoft BI Stack, AWS BI Stack, ETL/ELT Design, Data Quality Management

• Oversees and directs the work of Ad Tech Support Specialist and Business Analyst/ Project Lead positions, including creating an ongoing training and development plan
• Define, prioritize, and maintain a tactical roadmap for customer-facing applications, in alignment with strategic vision
• Daily Interactions with senior management to keep abreast of objectives
• Develop product strategy and vision for Ad Tech products in Delivery, Forecasting, Campaign management and post-campaign reporting by using an in-depth understanding
• Executes product development from conception to launch
• Serve as the domain expert for the area, with a deep understanding of the ad tech landscape, its table stakes, as well as differentiation
• Authors product requirements and user stories in conjunction with stakeholders, ensuring that market needs are met
• Ensures documentation of product requirements and business logic is accounted for and up-to-date
• Create buy-in for the product vision, both internally and with key external partners

Skills: Product Roadmapping, Ad Tech Expertise, Stakeholder Management, Product Strategy, Requirements Authoring, User Story Writing, Cross-Functional Leadership, Vision Alignment

• Design, maintain, and develop cloud-based data solutions that are well tested, monitored, and extensible
• Design system roadmaps and best practices to help guide data engineers in the right direction
• Assist in planning by being a strong technical voice and providing technical capacity assessments
• Provide code review, technical mentoring, and feedback to promote the team’s growth
• Hands-on with coding and development up to 70% of the time
• Automate manual processes by utilizing tools and technologies that can be applied across multiple initiatives
• Lead by promoting a culture of openness and collaboration
• Define the strategy, architecture and roadmap of the data platform
• Provide clear relationships and flows between different marketing technologies from a customer lifecycle standpoint 
• Delivery of analysis and reporting/ data visualization
• Accountable for integrity in data reporting and interpretation
• Develop data ingestion scripts, data joins to create data visualization dashboards
• Oversee and drive the execution of the data platform build from planning to delivery, with a strong focus on customizing solutions to meet regional needs
• Sustain support to ensure that projects meet established business objectives, time and budget constraints, and standards of technical quality

Skills: Cloud Data, Platform Strategy, Technical Leadership, Code Review, Process Automation, Data Architecture, Data Visualization, Data Integrity

• Lead role where the position defines and oversees how the organization captures, maintains, and applies data and information to support key business processes
• Implement the strategic direction for building data management programs and optimizing how the organization uses data both internally and externally
• Evaluate data that recognizes trends, call insights, and make recommendations to the executive leadership team to make recommendations to define business strategy
• Develop the data strategy and vision for building the analytic ecosystem to evaluate, acquire, integrate, and consume data that drives insights
• Define cloud strategy and lead cross-disciplinary teams to design and implement a scalable future state analytical platform architecture
• Assists with the development of strategies and coordinates the implementation that support the Organization's development plans and that capture new opportunities
• Partner cohesively with the broader Insights leaders across campus concerning the alignment capabilities
• Oversee the implementation of analytic methodologies including segmentation, predictive modeling, advanced statistical methods, regression, experimental design, etc.
• Oversee the sourcing and creation of partnerships with key analytical vendors who can provide specialized expertise to assist with solution development, while leading the in-house effort and managing CO interface
• Participate in the selection and management of cloud provider relationships

Skills: Data Strategy, Data Governance, Executive Insights, Analytics Leadership, Cloud Architecture, Predictive Analytics, Vendor Management, Cross-Functional Leadership

• Oversee project plans, timelines, and vendor relationships to ensure releases are delivered with the highest quality, on time and within budget
• Establish governance, manage technology priorities and develop a 3-5 year analytic roadmap for SJSU
• Define cloud strategy and lead cross-disciplinary teams to design and implement a scalable future state analytical platform architecture
• Partner with University stakeholders and be responsible for data analytics, custodianship, and infrastructure to ensure alignment with departmental data and analytics requirements to avoid conflicting activities, and develop the most efficient data analytics insights across the departments
• Identify, interpret, analyze and address critical business issues, questions and develop use cases
• Organize and create an environment that makes data and information accessible with appropriate channels of access controls
• Work with internal and external stakeholders to build a relationship of trust and play an advisory role in the use of data to improve performance and University-wide strategy formulation
• Develop and document clear, understandable plans, roadmaps and communication for business users, technical staff and IT groups
• Follow IT policies and standards for maintaining consistency and standards across the SJSU campus
• Lead and own the interaction with campus technical support staff and customers to provide reliable services

Skills: Project Governance, Analytics Roadmapping, Cloud Strategy, Data Stewardship, Business Analysis, Data Accessibility, Stakeholder Advisory, Service Delivery

• Participate in design discussions, create solutions, develop programs and ensure the successful delivery of business capabilities
• Take complete end-to-end ownership of one or more applications
• Translate business requirements and source system understanding into technical solutions
• Work with business partners directly to seek clarity on requirements and propose solutions
• Define solutions in terms of components, modules and algorithms
• Develop and implement the proposed solution
• Identify or develop software frameworks to be used
• Refactor existing solutions to make them reusable and scalable
• Come up with Coding and Design best practices
• Lead and mentor a small team, deliver tech talks to a wider audience
• Thrive in a self-motivated, internal-innovation-driven environment
• Adapt to new application knowledge and changes

Skills: Solution Design, End-to-End Ownership, Requirements Translation, Software Development, Framework Design, Code Refactoring, Best Practices, Technical Mentoring

• Collaborate with project teams, data science teams and development teams to drive the technical roadmap and guide the development and implementation of new data-driven business solutions
• Drive development effort End-to-End for on-time delivery of high-quality solutions that conform to requirements, and conform to the architectural vision
• Comply with all applicable standards
• Responsibilities span all phases of solution development
• Collaborate with senior technical staff and PM to identify, document, plan contingency, track and manage risks and issues until all are resolved
• Present technical solutions, capabilities, considerations, and features in business terms
• Build complex data products using multiple technologies across all phases of the development lifecycle, including design, coding, and testing in an Agile environment
• Use a variety of tools and techniques for data ingestion and egress between different databases, services, and platforms
• Identify opportunities for automation, optimization, and improvement of data products and processes
• Consult on cloud and big data technologies, capabilities, and approaches
• Work with partners across technology and the business to achieve project deliverables within defined timelines

Skills: Technical Roadmapping, End-to-End Delivery, Architectural Compliance, Risk Management, Technical Communication, Data Product Development, Data Integration, Cloud Consulting

• Design, build and launch extremely efficient and reliable data pipelines to move data across several platforms including Data Warehouse, online caches and real-time systems
• Provide data architecture that is flexible, scalable, and consistent for cross-functional use, and aligned to stakeholder business requirements
• Manage workflow orchestration and demonstrate strength in data modeling, ETL development, and data warehousing
• Build analytical tools to increase the productivity of Data Analysts, Data Scientists and Marketers
• Partner with BI, IT, Marketers and Data Scientists to understand data needs and assist them in accessing and leveraging key data sets
• Define SLA and acceptable time lags by data source, define QA process, and socialize resolution process to ensure data is flowing accurately through data creation to presentation layers
• Help the Marketing organization become a 100% data-driven organization by building a next-generation data platform that brings accurate and timely data to the Marketers
• Validate Data Engineering business data elements, organizational and business intelligence architecture designs for engineering functional areas from Dashboards, Data Lakes, Data Operations, ML- AI, and upstream/downstream intake and output processes
• Designs and builds the data strategies and roadmaps necessary to serve marketing analytics and data science needs

Skills: Data Pipelines, Data Architecture, Workflow Orchestration, ETL Development, Data Warehousing, Analytics Tools, Data Quality SLAs, Marketing Analytics

• Design, build, implement and maintain Data Migration processes
• Design, build, implement and maintain Data Integration and ETL/ELT pipelines
• Design, build, implement and maintain databases (Snowflake, Dynamics, PostgreSQL, MySQL/MariaDB, Oracle, Sybase)
• Design, build and maintain solutions incorporating the company's Data Lake
• Provide Business Level through to Technical Level analytical expertise for data-related aspects of IT projects
• Design, build, implement and support programs and applications for database management, data management and user interaction with various data sources
• Design and document the architectural components to transform raw transactional data into a consistent and coherent dataset suitable for BI use
• Ensure guidelines exist for integration, cleansing and data modelling including data warehouse structures (aggregation, federation, virtualization)
• Understand the data components to meet business requirements including currency, quality, granularity, velocity and structure

Skills: Data Migration, Data Integration, ETL/ELT Pipelines, Database Management, Data Lake Solutions, Data Architecture, Data Modeling, BI Enablement

• Leading by example to develop data pipelines that transform data from multiple sources from the data lake to higher-level features
• Refining the Agile backlog with other stakeholders and then ensuring the rollout of stories from the backlog to the team through the agile process (fortnightly sprints)
• Ensuring that Data Governance is followed and enhanced in areas of data quality, data monitoring, data architecture, data lineage, and PII
• Improving the data asset via the addition of new data sources or business views
• Upgrading the technology stack to create efficiency
• Operating in a fast-paced, iterative environment while remaining compliant with Information Sec policies/standards
• Collaborating with data scientists to map data fields to hypotheses and curate, wrangle, and prepare data for use in their advanced analytical models
• Lead a team of Data Engineers to drive continuous improvements
• Maintain and improve the AWS cloud infrastructure
• Design and implement data quality best practices
• Build and maintain data pipelines using Python and SQL

Skills: Data Pipelines, Agile Delivery, Data Governance, Cloud Infrastructure, Data Quality, Python SQL, Team Leadership, Analytics Collaboration

• Responsible for the development of software technologies that provide the data analytics used to drive the delivery of Hulu’s online streaming offerings
• Designing, developing, and implementing services and tools used by Hulu’s big data platform to solve complex data issues
• Building Hulu’s next-generation data analytics platform utilizing the most advanced big data technologies
• Solving complex data platform issues and exploring new technologies to provide innovative solutions
• Designing, developing, scaling, and improving the service and tools in Hulu’s unrivaled big data platform for the entirety of Hulu by using both Cloud and on-premise environments
• Implementing solutions using cutting-edge technologies
• Rewriting and enhancing Kafka, Presto
• Handling Couchbase and Memsql
• Giving back to the open source community
• Developing novel and scalable solutions to meaningful big data/Machine Learning/Artificial Intelligence technical problems and introducing new technologies

Skills: Big Data Platforms, Distributed Systems, Cloud Engineering, Streaming Technologies, Kafka Presto, NoSQL Databases, Scalable Architecture, Advanced Analytics

• Diagnosing and debugging issues in production environments
• Collaborating with Architects, Researchers, Program Managers, and Product Managers
• Utilizing programming (Scala/Java) and shell scripting skills
• Working with real-time processing infrastructure, including Kafka, Spark streaming, Couchbase, etc. 
• Utilizing experience in high-traffic and scalable distributed computing production systems
• Utilizing administration knowledge of the Hadoop ecosystem, such as HDFS, Hive, etc. 
• Using strong cloud infrastructure knowledge in AWS (Amazon Web Services)/Google Cloud
• Engaging in web UI design/development with React

Skills: Production Debugging, Distributed Systems, Scala/Java, Streaming Platforms, Big Data Ecosystem, Cloud Infrastructure, AWS/GCP, Web UI Development

• Set the direction for Artsy’s data infrastructure, establishing technology, tools and processes around quality and reliability
• Collaborate regularly with other engineers, data analysts, and product managers
• Help to hire, develop, and lead other data engineers
• Empower a data-driven culture by making high-volume activity data rapidly available for analysis
• Build and operate production pipelines and models
• Ingest and aggregate data from both internal and external data sources to build world-class datasets
• Transform the growing body of art market data collected into meaningful insights about artists, artworks, and trends
• Contribute to machine learning models that aid in ranking, classification, and predictive tasks such as recommendations and similarity

Skills: Data Infrastructure, Technical Leadership, Data Pipelines, Data Ingestion, Analytics Enablement, Machine Learning Support, Cross-Functional Collaboration, Data-Driven Culture

• Experience as a data engineer and BA 
• Experience with traditional data warehousing and ad technology 
• Proficient with Google Cloud Platform
• Proficient with Excel and PowerPoint
• Experience in Amazon Web Services, Snowflake, and BigQuery
• Must have good communication skills
• Experience as a data engineer (designing and supporting ETL pipelines)
• Extensive experience in SQL and database technology
• Strong understanding of either Python, C++, or Java
• Solid technical leadership qualities

Qualifications: BS in Computer Science with 4 years of Experience

• Experience as a Data Engineer
• Strong SQL skills
• Experience with a Data Warehouse (Dimensional modeling or other)
• Proficient with ETL jobs development, deployment and supporting through their lifecycle
• Hands-on work with AWS and good knowledge of its sub-components and services
• Hands-on experience with Python and PySpark
• Experience with the next AWS services such as S3, Step Function, Lambdas, Glue, Redshift, Athena
• Experience with Agile projects
• Good understanding of Software Development Lifecycle
• Ability to multitask, prioritize and execute tasks in a fast-paced environment
• Advanced analytical and troubleshooting skills

Qualifications: BS in Data Engineering with 5 years of Experience

• In-depth and hands-on experience in data modelling, building ETL pipelines, and Orchestration using either the Apache stack (Spark, HDFS, Airflow, etc.)
• Strong understanding of SQL
• Leadership and communication skills to communicate ideas to colleagues and senior stakeholders
• Hands-on experience with Google Cloud and/or experience building real-time analytics 
• Understanding of the financial domain, treasury, and liquidity management 
• Experience in working with multiple file systems including HDFS, SQL/ NoSQL databases (schema design and query optimization)
• Experience in distributed query engine (Athena/Presto/Impala/etc)
• Experience in data warehousing (Redshift/etc)
• Experience in data visualization tools (Metabase/Redash/etc)
• Experience in building a no-ops data engineering culture
• Experience working with FinTech/B2B startups

Qualifications: BS in Data Science with 7 years of Experience

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
• Experience/exposure in big data technologies (e.g., Spark, BigQuery, Redshift, Flink, Map/Reduce, HDFS, Pig, Hive, Presto, Airflow, Luigi, Kafka, Avro, Parquet)
• Experience building data infrastructure in the cloud (e.g., AWS, Google Cloud, Azure)
• Practical experience with Python and SQL 
• Ability to write, analyze, and debug SQLBuild processes supporting data transformation, data structures, metadata, dependency, and workload management
• Professional experience in a Data Engineering role
• Hands-on technical leadership style to fully understand and support the Data Engineering function within BI
• Profound understanding of databases (relational, column-based, NoSQL), DWH design, SQL querying and optimization
• Experience with big data tools and writing code for big data ETL pipelines using Spark/Scala/Hadoop
• Dash-boarding and storytelling skills
• Experience in Looker 
• Working knowledge of scalable BI&A infrastructure, APIs, workflow management tools, message queuing, stream processing, and ‘big data’ data stores

Qualifications: BS in Software Engineering with 6 years of Experience

• Professional work experience designing and implementing data pipelines in cloud environments
• Experience with AWS Cloud platforms, Python programming, and frameworks (e.g., Django, Flask, Bottle)
• Hands-on programming experience using Scala, Python, R, SAS, or Java
• Professional work experience on ETL pipeline implementation using AWS services such as Glue, Lambda, EMR, Athena, S3, SNS, Kinesis, Data-Pipelines, Pyspark, etc
• Knowledge or experience in architectural best practices in building data lakes
• Experience building conceptual, logical, and/or physical database designs
• Previous experience working with one or more databases like Snowflake, AWS Redshift, Oracle, SQL Server, or Teradata
• Expert-level knowledge of using SQL to write complex, highly optimized queries across large volumes of data
• Professional hands-on experience working with one or more ETL tools to build data pipelines/data warehouses
• Professional work experience using real-time streaming systems (Kafka/Kafka Connect, Spark, Flink or AWS Kinesis)
• Strong problem-solving and troubleshooting skills with the ability to exercise mature judgement
• Ability to build and maintain strong stakeholder relationships

Qualifications: BS in Information Technology with 8 years of Experience

• Experience coding in Python
• Knowledge in different orchestrators such as Elasticsearch, Splunk, Qradar, Demisto, Service Now
• Knowledge of designing and integrating with Data models
• Previous experience in the marketplace and Integration tools 
• Team player, accountable, dedicated and passionate
• Deep understanding of system design, data structures, and algorithms
• Experience with cloud services such as GCP/AWS/Azure
• Familiar with other cybersecurity solutions 
• Deep understanding of Google Cloud, AWS, GOlang programming language
• Able to manage the support of multiple application systems and their databases
• Able to define requirements, perform analysis and support application programming, testing and implementation tasks using T-SQL, Analysis Services, Reporting Services and SSIS
• Must be able to use project management skills to coordinate and manage tasks with users, IT Infrastructure and IT Analysis and Development units
• Experience working in an Agile environment (Scrum, Lean, Kanban)

Qualifications: BS in Computer Engineering with 5 years of Experience

• Understanding of Web Services protocols such as REST, SOAP, and API design
• Ability to use version control software such as GIT
• Working experience in Data Modelling
• Experience as an applications programmer on large-scale database management systems
• Experience with Linux, Python, XML, Redshift, JavaScript, Groovy, JSON
• Familiarity with AWS
• Experience with deployments to cloud / SaaS solutions
• Working knowledge of Agile concepts

Qualifications: BS in Applied Mathematics with 3 years of Experience

• Hands-on data engineering expertise and experience in building at least one Python/Spark/Scala-based data ingestion, transformation, and egress framework
• Working experience on Data Lake Implementations on Azure cloud / Big Data technologies
• Cloud experience in one or more Azure, AWS or GCP environments
• Expertise with modern data warehouse design patterns and tools
• Good understanding of data architecture principles including data modelling
• Should be able to tune Spark and Scala jobs for performance
• Deep understanding of distributed computing systems
• Should be familiar with Data Warehousing concepts and physical Data modelling techniques
• Able to stitch together a Real-time, Streaming, kappa and lambda solution
• Proficient with the latest Big Data tools/technologies like Hive, Hadoop, Yarn, Kafka, Spark Streaming
• Good knowledge of AZURE cloud data technologies (Spark, ADLS2, CosmosDB, AKS, AEH)
• Good temperament - building relationships and stakeholder management skills

Qualifications: BS in Statistics with 7 years of Experience

• Work experience in the Data Engineering field
• Proven experience working with Hadoop and Big Data processing frameworks (Spark, Hive, NiFi, Spark-Streaming, Flink, etc.)
• Experience building scalable, real-time and high-performance cloud data lake solutions
• Strong experience with relational SQL and programming languages such as Python, Scala, or Java
• Experience with source control tools such as GitHub and related CI/CD processes
• Solid understanding of Big Data streaming services such as Kinesis, Kafka, etc.
• Experienced with NoSQL data stores such as HBase, DynamoDB, etc.
• Experience provisioning RESTful API’s to enable real-time data consumption
• Experience working in AWS environment, primarily EMR, S3, Kinesis, Redshift, Athena, etc
• Experience with data warehouses/RDBMS like Snowflake and Teradata
• Experience with workflow scheduling tools like Airflow
• Strong understanding of algorithms, data structures, data architecture, and technical designs
• Proven track record to influence and communicate effectively with team members and business partners
• Ability to partner with teams in solving complex problems by taking a broad perspective to identify innovative solutions

Qualifications: BS in Information Systems with 8 years of Experience

• Working experience as a developer in the Data Warehouse discipline, working on MPP databases (Teradata, Snowflake, Redshift, Big Query, etc.)
• Proficiency in MPP databases, Data Warehouse design, ETL tools like DataStage or Informatica
• Experience leading teams of developers to deliver Data Warehouse Solutions
• Excellent SQL and hands-on scripting ability
• Ability to architect a BI/DW solution
• Excellent written and verbal communication skills
• Experience creating Enterprise Data systems on Azure or AWS
• Experience in agile principles
• Strong coding skills with Python
• Experience building platforms on cloud services 
• Solid software engineering best practices (CI/CD)

Qualifications: BS in Cloud Computing with 5 years of Experience

• Experience creating IaC for GCP data environments using Terraform or Deployment Manager
• Understanding of ML concepts and data preparation techniques to build ML data pipelines
• Hands-on experience in aspects of business intelligence and data engineering
• Experience leading a data engineering team
• Advanced understanding of dimensional modeling 
• Ability to build and optimize data pipelines, transformations, architectures, and data sets
• Strong knowledge in a variety of data engines such as SQL Server, MySQL and/or Redshift 
• Experience with data tools such as Datadog, Alation, Tableau and/or other reporting tools 

Qualifications: BS in Big Data Analytics with 4 years of Experience

• Progressive and relevant data engineering experience
• Working experience as a lead engineer, diagnosing complex issues, managing junior engineers, and owning the engineering architecture
• Proven background leading the design and creation of a delta lake or data warehouse
• Demonstrated knowledge of ETL/ELT best practices
• Advanced SQL to create data pipelines that solve complex business needs
• Experience with dbt
• Experience with Fivetran or Stitch
• Experience with a subscription business
• Excellent understanding of data pipelines in a Cloud environment
• Strong background in strategising and improving data architectures
• Previously worked within a modern data platform
• Experience with Python or Java and Spark
• Expert SQL Skills

Qualifications: BS in Artificial Intelligence with 7 years of Experience

• Experience in leading, mentoring, and training a team of data engineers
• Experience working with remote teams
• Experience with ETL tools like SQL, SSIS, AWS, Lambda, and Python
• Experience with data warehouse concepts, including Kimball methodology
• Experience with SQL Server and Redshift management
• Must have enthusiasm for deduction and problem-solving, with a logical and curious mind
• Ability to connect with colleagues
• Advanced skills in strategic planning, analytical and holistic problem-solving, project management, effective communication, and coordination of internal and external resources
• Strong interpersonal, communication, organization, and planning skills
• Ability to work effectively with faculty, staff, and senior administrators in areas other than technology to develop and implement appropriate uses of technology
• Ability to understand complex challenges and lead teams of technologists to deploy appropriate technological solutions that meet campus vision and mission
• Ability to lead, coordinate and influence the efforts of cross-functional teams

Qualifications: BS in Machine Learning with 8 years of Experience

• Must be able to communicate ideas both verbally and in writing to management, business and IT sponsors, and technical resources in language that is appropriate for each group
• Significant experience with at least one major RDBMS product
• Experience working with and supporting Unix/Linux and Windows systems
• Proficient in relational database modeling concepts and techniques
• Solid conceptual understanding of distributed computing principles
• Advanced knowledge in Visualization tools like Google Data Studio, Tableau, Looker, etc.
• Knowledge building and optimizing ‘big data’ data pipelines, architectures, and data sets
• Ability to build processes supporting data transformation, data structures, metadata, dependency, and workload management
• Advanced knowledge of systems development life cycle methodologies (Agile and Waterfall) to develop effective systems
• Advanced knowledge of application development, testing, and deployment processes and tools
• Strong analytic skills related to working with unstructured datasets

Qualifications: BS in Computational Science with 6 years of Experience

• Database administration experience with Microsoft SQL Server
• Data warehousing experience in utilizing the Microsoft BI Stack
• Experience with NetSuite and Workato 
• Experience with Monitoring, Performance Tuning, Security, and Configuration of SQL Server environments 2008 R2, 2012 and 2019
• Experience in Azure SQL and Power BI
• Experience in Azure Synapse Analytics
• Experience with high availability and backup/recovery solutions (i.e., Clustering, Log Shipping, Replication, AG, Backup/Recovery, etc.)
• Significant experience in the use of the T-SQL Language and stored procedures, triggers, SSIS, SSRS, and data modeling
• Ability to persuasively communicate complex concepts and programs across technical and non-technical audiences
• Excellent organizational, problem-solving and time management skills
• Exceptional analytical and critical thinking skills
• Strong interpersonal and diplomacy skills
• Knowledge and experience in all phases of the development life cycle

Qualifications: BS in Cybersecurity with 7 years of Experience