• Leading the entire software lifecycle including hands-on development, code reviews, testing, deployment, and documentation for batch ETLs.
• Coordinating data movement between systems and tools.
• Developing, automating and maintaining new data sources that help drive the business.
• Architecting a new modern event-driven architecture to fit the AWS processing model (EMR + Spark, S3).
• Working on Big Data technologies including Hadoop/Hive, PySpark, and Presto.
• Operating in an agile model leveraging scrum methodologies and Jira tools.
• Migrating existing data pipelines from on-prem regional data centers to AWS cloud.
• Support the loading and integrity of the data warehouse.
• Create data dictionary's and proper documentation on the data warehouse (Oracle DB)
• Work closely with the Data Analysts, business units and other infrastructure teams 
• Continuously improve the company’s various data processes and build new data solutions like reports and real-time dashboards.

Skills: Software Lifecycle Management, Data Coordination, ETL Automation, AWS Architecture, Big Data Tools, Agile Practices, Data Integrity, Dashboard Development

• Defining and building a data warehousing strategy on AWS
• Build an optimized data strategy to support OLAP reporting, Ad-hoc analysis and Data Science activities
• Creation and maintenance of data warehouse and/or data marts to support business data analysis and reporting
• Ensure best practices in data management are being followed
• Track work progress and report status via the issue-tracking system
• End-to-end responsibilities for designing and developing analytical data models, ETL processes, reports and dashboards in Oracle and Hadoop/Cloud Platform
• Run through project and business requirements- create end-to-end design including technical implementation
• Create and enhance data warehouse performance, using tuning techniques for MicroStrategy, Power BI and OBIEE
• Maintain standards for ETL processes
• Work with business stakeholders and translate requirements into ETL procedures
• Responsible for data governance ensuring effective data management throughout the group.

Skills: Data Warehousing Strategy, OLAP Reporting, Data Mart Development, Data Management Best Practices, Issue Tracking, Analytical Data Modeling, ETL Process Design, Data Governance

• Learn and become an expert in the data domain and current data models.
• Define and implement data pipelines to lift and shift OLTP data (Mongo and Neo4j) to the Snowflake data lake.
• Define and implement efficient and unit-tested DBT (Data Build Tool) transformations of data into reporting schema tables.
• Design new data structures for features (OLTP and OLAP)
• Optimize workloads to reduce cost and improve performance
• Develop monitoring over BI infrastructure
• Translate business requirements to technical specifications.
• Create and maintain data dimensions and aggregates
• Develop simple reports on Tableau
• Load and validate dimensions and measure stored procedures
• Perform all application unit and system testing

Skills: Data Domain Expertise, Data Pipeline Implementation, DBT Transformations, Data Structure Design, Workload Optimization, BI Infrastructure Monitoring, Business Requirements Translation, Tableau Reporting

• Gain a thorough understanding of the organization’s business processes and how they translate to analytical data that can be used for reporting.
• Understand internal and external data sources, and know how, when, and which to use.
• Design, develop, and implement a modern enterprise data warehouse, on-prem and in the cloud.
• Build analytical datasets to support ad-hoc business needs.
• Analyze, document, and enhance current ETL and reporting processes.
• Assist with migration from legacy systems and older technologies to a modern data warehouse and ETL solutions.
• Identify data integrity issues, recommend remediation solutions, and work with stakeholders to resolve them.
• Work with the BI and Analytics departments to create short-term tactical solutions to achieve long-term objectives and an overall data management roadmap.
• Assist in the planning and development of the cloud BI environment, which uses Data Factory, Data Lake, and Data Bricks and is related to the ETL activities, including process scheduling, data transformation, archiving, and warehousing of data.
• Design a modern data warehouse based on the requirements of the analytical and reporting systems with accuracy and performance in mind, on-prem and in-cloud.
• Ensure the analytical data, including live feed and historic data, is prepared for reporting within the SLT requirements and boundaries.

Skills: Business Process Analysis, Data Source Management, Enterprise Data Warehouse Development, Analytical Dataset Creation, ETL Process Enhancement, Legacy System Migration, Data Integrity Remediation, Cloud BI Planning

• Liaise with the infrastructure team, application team, and BI/reporting team regarding the ETL data flow, data cleansing, and data delivery.
• Assess and determine governance, stewardship, and frameworks for managing data flow from all data sources to BI/analytical systems.
• Design, develop and enhance data pipelines.
• Assist with selecting and implementing the appropriate tools, software, applications, and systems to support BI/reporting systems.
• Assist with the mapping of data sources, data movement, interfaces, and analytics, to ensure data quality.
• Collaborate with data source owners and BI system analysts for all reporting project needs.
• Develop and implement key components to create testing criteria to guarantee the fidelity and performance of the analytical data sources.
• Document the ETL activities to maintain a current and accurate view of the data flow for the BI/analytical systems.
• Identify and develop opportunities for data reuse, migration, or archiving.
• Manage and maintain a secured ETL flow using up-to-date best practices at all times.

Skills: Data Flow Liaison, Governance Framework Assessment, Data Pipeline Development, BI Tool Implementation, Data Mapping and Quality, Collaboration with Stakeholders, Testing Criteria Development, ETL Documentation

• Respond to day-to-day questions and issues around the Trade Surveillance and TRR process.
• Work closely with vendors for Trade Surveillance reporting (possibly Nasdaq Smarts)
• Work with the in-house reporting team to assist in building dashboards and statistical reporting for the compliance team.
• Support the Front Office team when the files change.
• Collaborate with end users like Compliance and help with BAU.
• Define solutions paying particular attention to ensuring technical requirements have been factored in
• Develop efficient ETL routines using advanced SSIS as well as Oracle database technologies such as PL/SQL external tables
• Data Extraction from Source systems using ingestion techniques of Azure Data Factory
• Work with the overnight batch processes using schedule software, Control-M
• Work with wider Technology teams to ensure development and testing are coordinated and best practices are followed
• Help define test cases and work closely with users assisting them with testing bug fixes or new features and functions

Skills: Trade Surveillance Support, Vendor Collaboration, Dashboard Development, Front Office Coordination, Technical Solution Definition, ETL Routine Development, Data Extraction Techniques, Test Case Definition

• Building large-scale databases
• Data modeling (Data Vault 2.0 and Star Schema), data management, ETL, and BI
• Perform ongoing monitoring, automation and refinement of BI solutions.
• Contributes to the design, automation, acquisition, transformation and data loading processes in a high volume, high availability data warehouse environment
• Manages the automation and operations of the data warehousing loading process
• Contribute to the design of the data warehouse architecture
• Provides production support to solve immediate problems and keeps databases in production
• Analyses information requirements of customers and supports teams and contributes to the design of the best technical solutions
• Collaborate with business and technical partners to understand and evaluate their needs for data from the data warehouse to understand and evaluate their needs for data from the data warehouse.
• Technical implementation of the data warehouse
• Participates in testing of the data design, tool design, and data extracts

Skills: Large-Scale Database Building, Data Modeling, BI Solution Monitoring, Data Warehouse Design, Automation Management, Production Support, Information Requirement Analysis, Technical Solution Collaboration

• Design and develop dimensions and fact tables using data warehousing best practices.
• Create physical and logical data models.
• Analyze systems and data using a variety of languages and procedures.
• Provide input and guidance into the data modeling architecture, strategy, and delivery.
• Accept ownership for creating and maintaining the enterprise data dictionary.
• Develop and maintain ETL/ELT tools, layers, and data lineage.
• Execute good data practices to normalize, standardize, and categorize nomenclature across various data sources.
• Maintain supporting documentation such as ERDs, metadata diagrams, and process flowcharts.
• Create test plans and data auditing strategies to ensure warehouse accuracy, currency, and dependability.
• Collaborate with data management to test, clean, and standardize data to meet business requirements.
• Work cross-functionally with various departments including business stakeholders and technical personnel to exchange ideas.

Skills: Data Warehousing Design, Dimension Development, Data Modeling, Data Architecture, Data Dictionary Management, ETL Development, Data Normalization, Cross-Functional Collaboration

• Data engineering/analytics experience
• Must have a passion for data and helping the business turn data into information and action
• Data modeling and ETL development experience
• Ability to initiate, drive, and deliver robust data solutions
• Ability to communicate effectively with business leaders and engineers
• Strong in SQL, databases, and data modeling methodologies (Kimball, Inmon or DataVault)
• Experience with cloud data warehousing technologies (Snowflake or Redshift) and MPP systems
• Knowledgeable in scripting languages (Python, .Net, Perl, etc.)
• Be a structured thinker and effective communicator.
• Ability to operate effectively in a team atmosphere within a fast-paced development schedule

Qualifications: BS in Software Engineering with 2 years of Experience

• Proven work experience in data warehousing, ideally in an SQL environment and large data sets in an enterprise environment
• Knowledge of logical and physical model design and implementation
• Experience in data warehouse schema and dimensional modeling techniques to support business consumption of data
• Experience in Azure data components including, Azure SQL Data Warehouse and Azure Analysis Services
• Strong analytical skills with the ability to adopt a logical approach to solving problems
• Strong skills in developing code, testing for quality assurance, administering and monitoring of databases
• Ability to create and maintain sets of reference architecture documentation
• An organized and proactive approach with an emphasis on attention to detail and accuracy
• Experience in Scaled Agile Framework.
• Strong problem-solving and analytical skills.

Qualifications: BS in Information Technology with 3 years of Experience

• Experience performing data warehouse architecture development and management
• Experience with technologies such as SQL Server 2008, as well as with newer ones like SSIS and stored procedures
• Experience developing codes, testing for quality assurance, administering RDBMS, and monitoring of database
• High proficiency in dimensional modeling techniques and their applications
• Strong analytical, consultative, and communication skills
• The ability to make good judgments and work with both technical and business personnel
• Experience with Tableau, QlikView, Information Builders, and other reporting and analytical tools
• Working knowledge of SAS and R code used in data processing and modeling tasks
• Experience with Microsoft Azure and Amazon AWS computing platforms
• Strong experience with Hadoop, Impala, Pig, Hive, YARN, and other “big data” technologies.

Qualifications: BS in Business Information Systems with 6 years of Experience

• Prior e-commerce experience
• Hands-on experience with a modern programming language (Scala, Python, Java), Spark/pyspark
• Recent hands-on SQL programming experience in a Big Data environment
• Working experience with Hadoop/Hive
• Experience working in the AWS cloud landscape
• Experience developing and maintaining ETL applications and data pipelines using big data technologies
• The ability to manage multiple stakeholders with excellent communication and interpersonal skills
• Understanding of full software development life cycle, agile development, and continuous integration.
• Excellent understanding of data warehousing and modeling concepts (E.g., Star and snowflake schemas).
• Ability to model data and develop reporting solutions from scratch.

Qualifications: BS in Computer Engineering with 4 years of Experience

• Experience designing and delivering large-scale, 24-7, mission-critical data pipelines and features using modern big data architectures
• Hands-on experience in Python and SQL.
• Experience working in Redshift and AWS Lambda.
• Strong understanding of ETL processing with large data stores
• Strong data modeling skills (relational, dimensional and flattened) and analytical SQL skills, with attention to detail
• Intermediate knowledge of BI best practices, relational structures, dimensional data modeling, structured query language (SQL) skills, data warehouse and reporting techniques
• Experience working with analytical presentation layers such as Dashboards, Reporting
• Excellent problem-solving skills
• The ability to work individually and in a matrix environment
• Strong communication skills and fluency in verbal and written English 

Qualifications: BS in Mathematics with 2 years of Experience

• Relevant data engineering work experience
• Hands-on experience with Microsoft/Azure Stack SSIS, SQL, ADF, etc.
• Possess strong analytical skills with the ability to analyze raw data, draw conclusions, and develop actionable recommendations
• Experience with the Agile development process preferred
• Hands-on experience with Azure data factory V2, Data Flows, Azure Databricks, Snowflake, Azure Data Lake, Azure analysis services and Cosmos DB
• Experience working with Python or Scala
• Understanding of continuous integration and continuous deployment on Azure
• Experience with large-scale data lake or warehouse implementation on any of the public cloud (AWS, Azure, GCP)
• Have excellent interpersonal and written/verbal communication skills
• Manage financial and company information in a confidential and professional manner

Qualifications: BS in Computer Science with 5 years of Experience

• Experience in database engineering and architecture.
• Experience working with AWS services like ECS, Lambda, S3, RDS, RedShift, DynamoDB, SQS, SNS, and Cognito
• In-depth knowledge of Structured Query Language (SQL).
• Familiarity with Analytical/Reporting Solutions like Tableau, Power BI
• Extensive experience with database technologies and architecture.
• Sound knowledge of best practices in database engineering and data security.
• Strong organizational skills and attention to detail.
• Exceptional problem-solving and critical thinking skills.
• Excellent collaboration and communication skills.
• Build positive working relationships with employees at all levels within the organization

Qualifications: BS in Mathematics with 4 years of Experience

• Experience in IT of building data engineering pipelines on Big Data platforms.
• Extensive experience with enterprise data management, data warehouse, data modeling, Business Intelligence, and data integration.
• Expertise in SQL and stored procedures.
• Experience in using Control-m to schedule data engineering workflows.
• Experience in working on Azure SQL Data warehouse (Synapse) and Azure analysis service.
• Experience in designing solutions for multiple large data warehouses
• A good understanding of cluster and parallel architecture as well as high-scale or distributed RDBMS and/or knowledge of NoSQL platforms.
• Extensive experience in translating, loading and presenting disparate datasets in multiple formats/sources including JSON, XML, etc.
• Demonstrate a high level of written and oral communication skills.
• Proven high level of initiative, drive and enthusiasm with excellent time management and an ability to work under pressure.

Qualifications: BS in Management Information Systems with 3 years of Experience