Data Engineer

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Who You Are and What You'll Do:

The data engineer will work as part of the data services team reporting to the Director Data Engineering. They will be primarily responsible for implementing ETL/ELT processes and data integrations that populate Kimball style star schemas using a variety of source data on multiple data warehouse implementations supporting a product. They will also participate in the requirements gathering process and assist with designing the business processes and dimensional models. The candidate will have a deep understanding of both OLTP and star schemas. Further, they will do deep analysis on source data to determine the feasibility of using this data to solve business needs. The resulting processes should be scalable, efficient, auditable and as re-usable as possible.

 What You’ll Do Day to Day:

• Production support of daily running ETL processes.
• Develop, design, optimize and maintain ETL/ELT processes.
• Design and develop stored procedures, functions, views and triggers to be used during the ETL process.
• Perform data profiling and source to target mappings (while capturing ETL and business metadata) for populating Kimball style dimensional models.
• Write scripts for automated testing of data in the target facts and dimensions.
• Capture audit information during all phases of the ETL process.
• Write and maintain documentation of the ETL processes including process flow diagrams.
• Conduct appropriate functional and performance testing to identify bottlenecks and data quality issues.
• Be able to implement slowly changing dimensions as well as transaction, accumulating snapshot, and periodic snapshot fact tables.
• Collaborate with business users, other data services team members, and other developers throughout the organization to facilitate everyone’s understanding of issues that affect the data warehouse.
• SQL Query optimization
• An understanding of the Software Development Life Cycle (SDLC) and Agile Development processes.

Knowledge, Skills and Experience That You Will Need to Be Successful in This Role:

• 3-5 years of experience with data warehousing and business intelligence projects
• 3-5 years of experience with relational databases (e.g., SQL Server , Oracle or Postgres)
• Experience pulling data from a variety of data source types
• Dimensional modeling experience preferably with a modeling tool such as Toad Data Modeler, ERwin, Embarcadero, ER/Studio Data Architect etc.
• Experience working with large data sets, tables containing greater than a billion rows
• Experience supporting and troubleshooting production ETL process issues.
• Strong experience working with SQL (Snowflake, Oracle, Postgres) and query optimization.
• Familiarity with the Kimball lifecycle and strong understanding of Dimensional Data Modeling.
• Experience with Object Oriented Programming Languages such as Python, C# or JavaScript

Additional Knowledge, Skills and Experience That Will Help You Stand out as a Candidate:

• Experience working with Snowflake is a huge plus
• Cloud Experience with Azure or OCI
• Big Data experience
• Data Replication (Kafka, Goldengate, HVR, Qlik Replicate)
• Qlik Data Integration Platform (Replicate, Compose)
• SQL Server 2017-2019 and the Microsoft BI stack
• Oracle 12c and above
• Postgres 9.6 and above

We are diverse and proud of it. We don’t just accept differences – we embrace,?share,?and celebrate?them!