Job Summary:

• Lead the data engineering team and report directly to the VP of Data
• Spearhead efforts to build a modern data platform to satisfy Penta’s huge ambitions
• Define the team’s priorities and be an ambassador for data engineering to the wider company
• Oversee data architecture and make key decisions about tools and methodologies
• Mentor the other team members and help them grow professionally
• Expand technical skills and learn many new things
• Work closely with colleagues on the data team on a variety of cross-functional projects
• Act as a mentor to the more junior members of the team
• Build, develop and maintain pipelines & features.
• Build out the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using Python, SQL, and Spark.
• Take ownership and responsibility for the data produced by the data pipelines.

Skills on Resume: 

• Data Engineering (Hard Skills)
• Team Leadership (Soft Skills)
• Data Architecture (Hard Skills)
• Mentorship Ability (Soft Skills)
• Pipeline Development (Hard Skills)
• Python Programming (Hard Skills)
• Cross-Functional Collaboration (Soft Skills)
• Problem Ownership (Soft Skills)

Job Summary:

• Develop a data engineering framework with cloud native approach.
• Quickly understand the current landscape of data and provide recommendations on building future data products.
• Establish data pipeline patterns, provide recommendations and tradeoffs 
• Deploy vendor technologies for data replication, data distribution, data streaming.
• Adhere to data protection requirements including data access, retention, residency and de-identification.
• Develop and maintain data flow and data sharing with internal and external systems.
• Create data validation checks and scripts to ensure high data quality and availability.
• Design and develop secure software in partnership with other engineering teams onshore and offshore.
• Keep a pulse on the industry, and research, evaluate and recommend new technologies, tools and frameworks for high volume data processing.
• Provide technical guidance and coaching to other team members

Skills on Resume: 

• Cloud Native (Hard Skills)
• Data Pipeline (Hard Skills)
• Vendor Technologies (Hard Skills)
• Data Protection (Hard Skills)
• Data Validation (Hard Skills)
• Secure Software (Hard Skills)
• Industry Research (Soft Skills)
• Technical Guidance (Soft Skills)

Job Summary:

• Develop and improve existing data services as well as identify opportunities for improved efficiency and performance.
• Investigate and resolve issues arising from the data backend platform services.
• Architect, design and implement features in line with new products and platform road maps.
• Work as part of a cross-functional team in collaborative design and development projects, serving as an advisor and influencer in the area of data engineering.
• Ensure that all aspects of development work conform to industry best practices in line with aspects of CI/CD and TDD.
• Improve operational processes and documentation.
• Take a step back and think about the bigger picture and then challenge the needs without creating friction.
• Partner with Data Engineers, Data architects, domain experts, data analysts and other teams to build foundational data sets and visualisations that are trusted, well understood, aligned with business strategy, and enable self-service.
• Support and maintain analytics tech ecosystem (ETL and BI tools)
• Assist with the configuration of real-time datasets in Moata (using Python, Azure and SQL)
• Document data pipelines and data lineage.
• Continuously identify areas of improvement and ensure application of standards and best practices

Skills on Resume: 

• Data Services (Hard Skills)
• Issue Resolution (Soft Skills)
• Platform Architecture (Hard Skills)
• Cross Functional (Soft Skills)
• CI/CD (Hard Skills)
• Process Improvement (Soft Skills)
• Data Collaboration (Soft Skills)
• ETL Tools (Hard Skills)

Job Summary:

• Build, maintain ETL pipelines from the business database to the data warehouse/ lake
• Build, maintain internal data platform services that support Analytics and Data Science
• Enhance and optimize existing data platform services
• Translate business requirements into data solutions
• Collaborate with the SMEs from the Service Support teams to understand the current data workflows and help design autonomous pipelines for conversational AI data ETL.
• Contribute to the data engineering solution design, usually in collaboration with business analysts, platform architects, security architects and product owners.
• Work closely with other software engineers in a hands-on fashion to implement the solutions in a programming environment
• Take on the role of data engineer of a complex reporting system, currently based on Oracle Exadata and Oracle BI, that is about to move to Azure infrastructure.
• Help drive decisions on the future cloud-based architecture of the application.
• Work hands-on on complex Azure-based developments.
• Help set up stable DevOps processes based on industry best practices.

Skills on Resume: 

• ETL Pipelines (Hard Skills)
• Data Platform (Hard Skills)
• Business Translation (Soft Skills)
• Data Collaboration (Soft Skills)
• Programming Environment (Hard Skills)
• Cloud Architecture (Hard Skills)
• Azure Development (Hard Skills)
• DevOps Processes (Hard Skills)

Job Summary:

• Collaborate directly with senior-level executives, process owners and technical teams within each customer to understand goals, objectives and requirements and translate them into technical requirements
• Understand how business processes work and create data models for those processes
• Analyze and organize raw data
• Connect the platform with the customer’s on-premise/ Cloud ERP & IT systems
• Extract and transform customers’ data and load them into the platform
• Design process and customer-specific dashboards, analyses and reports
• Perform ETL, interpret trends and patterns
• Drive analytics/EA service delivery with a small team and limited duration
• Recommend different ways to improve data quality and reliability constantly

Skills on Resume: 

• Executive Collaboration (Soft Skills)
• Business Processes (Hard Skills)
• Data Analysis (Hard Skills)
• System Integration (Hard Skills)
• ETL Processing (Hard Skills)
• Dashboard Design (Hard Skills)
• Team Leadership (Soft Skills)
• Data Quality (Hard Skills)

Job Summary:

• Build, test and ship well-engineered features and enhancements
• Design, support, maintain and upgrade highly performant and tested APIs and internal services using tools like Python, Celery, Kubernetes, MySQL, PostgreSQL, Mongo, Redis, AWS Redshift
• Articulate a long-term vision for maintaining and scaling systems
• Work with other engineers, product managers, designers and company leadership to turn vision into a concrete roadmap every quarter and to help develop an amazing experience for agency & brand customers.
• Translate business, analytics and reporting requirements into scalable solutions
• Conduct code reviews, lead mid- and low-level design efforts
• Design and build a data analytics and reporting platform in the cloud
• Develop automated, scalable, near-real-time data processing pipelines
• Implement a data quality gate to ensure the accuracy of ingested data
• Mentor junior and medior members of the team to follow best practices. 

Skills on Resume: 

• API Development (Hard Skills)
• System Scaling (Hard Skills)
• Cross Functional (Soft Skills)
• Business Translation (Soft Skills)
• Code Reviews (Hard Skills)
• Cloud Analytics (Hard Skills)
• Data Pipelines (Hard Skills)
• Team Mentorship (Soft Skills)

Job Summary:

• Designs, develops, configures, debugs/tests, implements, maintains, and documents BI solutions and processes using appropriate toolsets
• Ensures development standards and best practices are followed and adopted including source control, clean code, standards, techniques & analysis
• Ensures all code is version controlled and work is clearly documented and centrally located, setting and maintaining high professional standards
• Ensure all solutions are appropriately optimized and deliver solutions against challenging timescales with quality
• Produces coherent, reliable, and working technical documentation
• Peer reviews team members work as part of the release process
• Ensures the provision of a stable environment and continuity of service
• Design and support the construction of a database system for ingesting and integrating disparate data systems
• Recommend optimal data models for data ingestion and distribution
• Develop and maintain data models for the integrated data sets
• Perform data quality engineering, metadata model development, data warehouse design, data governance, and data security

Skills on Resume: 

• BI Solutions (Hard Skills)
• Development Standards (Hard Skills)
• Version Control (Hard Skills)
• Technical Documentation (Hard Skills)
• Peer Review (Soft Skills)
• Database Design (Hard Skills)
• Data Modeling (Hard Skills)
• Data Governance (Hard Skills)

Job Summary:

• Designing and developing highly available and performance-critical APIs.
• Building and managing microservices and data processing workload in Kubernetes environments.
• Leading designs of major software components and systems.
• Driving adoption of best practices in code health, testing, and maintainability.
• Designing, developing, testing, deploying, maintaining and improving software.
• Supporting production systems.
• Working closely with a wider Engineering team and contributing to improvement initiatives.
• Championing & assisting with the implementation of labeling infrastructure, data management and discovery systems.

Skills on Resume: 

• API Design (Hard Skills)
• Microservices Management (Hard Skills)
• Software Architecture (Hard Skills)
• Code Quality (Hard Skills)
• Software Development (Hard Skills)
• Production Support (Hard Skills)
• Team Collaboration (Soft Skills)
• Data Management (Hard Skills)

Job Summary:

• Working with large data sets and responsible for data acquisition and model development.
• Designing, developing, and deploying statistical and predictive models into production, contributing to projects focused on several different financial product types.
• Design and build data and software solutions that are performant, reliable and testable
• Research and establish solution design patterns
• Support production and be part of an on call rotation
• Continuously improve the quality of development, deployment, testing, and operational processes
• Work with business customers and data analysts to define detailed requirements from broader business challenges.
• Translate those requirements to logical and physical models that satisfy analytical needs.
• Perform data profiling and analysis to assess data quality patterns, recommend data cleansing rules, conforming data standard rules and matching algorithms.
• Own the system architecture and infrastructure of Google Cloud Data Warehouse and other related GCP services.
• Assist ETL and BI developers with complex query tuning and schema refinement.

Skills on Resume: 

• Data Acquisition (Hard Skills)
• Predictive Modeling (Hard Skills)
• Solution Design (Hard Skills)
• Production Support (Hard Skills)
• Requirement Translation (Soft Skills)
• Data Profiling (Hard Skills)
• Cloud Architecture (Hard Skills)
• Query Optimization (Hard Skills)

Job Summary:

• Use Python, SQL, and R to improve upon a best-in-class data pipeline and develop workflows
• Contribute to cloud-first services that improve reporting, analysis, and metrics collection efforts
• Use agile software development processes to iteratively make improvements to back-end systems
• Mold front-end and back-end data sources to help draw a more comprehensive picture of user flows throughout the system
• Deliver on detailed specifications for business intelligence and reporting needs
• Contribute and further develop a data-driven culture
• Work with product and engineering in cross-functional teams to deliver on improvements to systems
• Program SQL databases for deployment and use at local sites worldwide
• Deploy big data IT infrastructure on the shop floor and in labs
• Develop Power BI dashboards for manufacturing and engineering analytics

Skills on Resume: 

• Python Programming (Hard Skills)
• Cloud Services (Hard Skills)
• Agile Development (Soft Skills)
• Data Integration (Hard Skills)
• Business Intelligence (Hard Skills)
• Cross Functional (Soft Skills)
• SQL Programming (Hard Skills)
• Dashboard Development (Hard Skills)

Job Summary:

• Manage and ensure the AWS platform are always available, fast and highly scalable to accommodate unprecedented demand
• Design, build, deploy and manage scalable and reliable ETL pipelines to ingest data from various data sources
• Build a robust in-house platform to support analytics and data science
• Manage and process large amounts of data in near real-time to deliver up-to-date metrics
• Drive continuous improvements in the efficiency and flexibility of platform and services requirements. 
• Keen on learning and implementing best practices on cloud computing technologies
• Program data analytics and data visualization applications in Python
• Work on applications in the big data platform built on technology like Python, Cassandra, Hadoop and Neo4j
• Help to build out a new Google Cloud data platform and collaborate on architectural patterns for it with the Data Engineering team
• Support the development of machine learning models with productionizing, monitoring and alerting tools

Skills on Resume: 

• AWS Management (Hard Skills)
• ETL Pipelines (Hard Skills)
• Data Platform (Hard Skills)
• Real Time (Hard Skills)
• Continuous Improvement (Soft Skills)
• Python Programming (Hard Skills)
• Cloud Computing (Hard Skills)
• Machine Learning (Hard Skills)

Job Summary:

• Work closely with other engineers on the team to add and enrich data sets, manage storage and retrieval, and help scale analysis components that handle extremely large data sets. 
• Design, build, test, and deliver the underlying data management system that feeds the user-facing product components that customers use to protect software 
• Seize other opportunities to contribute to various other areas across the software stack 
• Curate and deliver information in a variety of forms to secure the software ecosystem 
• Professional experience in data engineering design, development, and implementation  
• Passionate about data science and building solutions to make data more accessible to customers 
• Proficiency or willingness to learn programming languages such as Rust, Python, Scala or similar languages 
• Excited to drive high-value, high-quality projects quickly to completion in a fast-paced startup environment 
• Familiarity with data structures, data modeling, data analysis and other technical tools

Skills on Resume: 

• Data Management (Hard Skills)
• Software Delivery (Hard Skills)
• Cross Domain (Soft Skills)
• Information Curation (Hard Skills)
• Data Engineering (Hard Skills)
• Programming Languages (Hard Skills)
• Project Execution (Soft Skills)
• Data Modeling (Hard Skills)

Job Summary:

• Architect, build, and refine data infrastructure technologies, using a development workflow, the outcome of work will drive decisions that affect billions of dollars of transactions
• Build and refine a fault-tolerant data ingestion pipeline into data warehouse, while helping guide the decisions about the future of data infrastructure
• Work with engineers and product managers to analyze edge cases, clear ambiguities, and plan for architectural scalability
• Write complex and efficient queries to transform raw data sources into easily accessible models for teams (e.g., Product, Growth, Finance, Risk)
• Write, update, and maintain ETL jobs across data pipelines
• Implement continuous improvements using the company's existing tools/technologies, which include SQL, Airflow, Python, Docker/Kubernetes, Looker and others such as Terraform and Apache Beam.
• Build data pipelines to integrate systems and move data into the data warehouse. 
• Use Amazon Redshift, Apache Airflow, Fivetran, Mule ESB, Python, and Bash, among other tools.
• Collaborate with data analysts across the business to build the tables and tools it need to support better decisions.
• Integrate data flows between operational systems, and build tools for data reconciliation

Skills on Resume: 

• Data Infrastructure (Hard Skills)
• Ingestion Pipelines (Hard Skills)
• Architectural Planning (Soft Skills)
• Complex Queries (Hard Skills)
• ETL Maintenance (Hard Skills)
• Continuous Improvement (Soft Skills)
• Cloud Tools (Hard Skills)
• Data Collaboration (Soft Skills)

Job Summary:

• Maintain full ownership of critical data assets and related analytics tools and perform quality checks to preserve data integrity.
• Design and build data pipelines that transform and persist data for various analytics use cases,
• Ensuring the completeness, consistency, and security of the data.
• Develop processes to improve data quality by monitoring data feeds and calculated analytics.
• Find innovative solutions to ingest and process new data sources using open source technologies, agile-based development processes, and cloud computing.
• Collaborate with team members to create a consistent approach to the loading, updating, and enriching of datasets.
• Design, install and maintain the Python and SQL Server database environments in support of financial services applications and products.
• Work on large database implementations (AWS / Azure experience) with the ability to maintain
• Create documentation for standards and best practices for robust database operations.
• Navigation of data tools on AWS (Kinesis, Glue, Redshift, Athena, Lambda, EMR, RDS, Aurora) and/or Azure (Blob Storage, Data Factory, Data Warehouse).

Skills on Resume: 

• Data Ownership (Hard Skills)
• Data Pipelines (Hard Skills)
• Data Integrity (Hard Skills)
• Data Quality (Hard Skills)
• Cloud Computing (Hard Skills)
• Team Collaboration (Soft Skills)
• Database Management (Hard Skills)
• AWS Azure (Hard Skills)

Job Summary:

• Design and develop enterprise business intelligence, data warehousing and reporting solutions
• Develop and implement ETL processes, reports and queries in support of business analytics
• Develop & implement ETL processes
• Propose and design data models and data marts to facilitate the use of data from multiple data sources
• Conduct data analysis and data profiling
• Write unit tests and automated testing scripts
• Develop and design database objects, such as tables, indexes, constraints, etc.
• Proactively analyze and bring forth ideas for continuous improvement
• Provide technical and business knowledge support to the team
• Understand the company's operational data models, troubleshoot data flow issues, and improve system reliability and fault-tolerance
• Create strong partnerships with stakeholders

Skills on Resume: 

• Business Intelligence (Hard Skills)
• ETL Development (Hard Skills)
• Data Modeling (Hard Skills)
• Data Analysis (Hard Skills)
• Automated Testing (Hard Skills)
• Database Design (Hard Skills)
• Continuous Improvement (Soft Skills)
• Stakeholder Management (Soft Skills)

Job Summary:

• Designing and delivering data models/schemas
• Designing, building and maintaining data pipelines that create efficient data science and data analyst data marts, ensuring solutions are optimized for processing of typical queries and reducing repetitive processing
• Identifying and implementing ways to increase efficiency and improve data reliability through automation
• Completing all relevant testing to ensure code is de-bugged and the data marts and tools are robust and accurate
• Recommending on how data should be structured to deliver an optimum user experience at the right speed while minimizing platform cost
• Working closely with other data team members to help ensure the data format and quality to design and build interactive self-service dashboards and tools that are highly engaging and meaningful to internal stakeholders
• Using tools such as Power BI, SQL, Hive, Spark, and others
• Translating large volumes of data into meaningful and appealing ways to users, which drives insights and action
• Defining the metrics, KPIs and data structures required to support visualizations

Skills on Resume: 

• Data Modeling (Hard Skills)
• Data Pipelines (Hard Skills)
• Process Automation (Hard Skills)
• Code Testing (Hard Skills)
• User Experience (Soft Skills)
• Dashboard Development (Hard Skills)
• Data Visualization (Hard Skills)
• KPI Definition (Hard Skills)