We are seeking a Senior Data Engineer to contribute to both design and hands-on implementation of reporting and analytics data models in our data warehouse, maintain and develop ELT pipelines, and contribute to data governance efforts across teams.

Requirements:

You have 7+ years of experience in data, analytics, and data engineering with the following areas:

• Strong SQL and Python background and can write well-structured, composable data transformations in SQL

• Knowledge of data modeling techniques and approaches (e.g. normalization/denormalization, Star Schema, Snowflake Schema, One Big Table, Slowly Changing Dimensions) and can discuss and implement the best approach for a given use case

• Experience with AWS - S3, EC2, IAM, etc

• Worked with modern data warehouses, e.g. Spark / Databricks, Snowflake, BigQuery, or Redshift

• Solid knowledge of DBT as part of a analytical engineering stack

• Collaborated with product organizations and data science teams to understand requirements and support user stories and analytics use cases in data models and pipelines

• Comfortable with data dictionary and data catalog tooling and fully embrace the importance of writing quality, useful documentation

• Implemented data quality tests to confirm the validity of data

• Experience using Git and a collaborative development process

• Familiarity with U.S. healthcare system and have worked with healthcare data before in a pharma/payer/consulting or similar context

• Working knowledge in medical claims processing a must

Bonus points for:

• Spark experience, particularly on Databricks or similar platform

• Worked in both OLTP and OLAP environments

• Startup experience

• Used Gitlab CI/CD or similar platforms (Github Actions, CircleCI, etc)

• Prior experience in analytics and or data science

• Experience working with reporting/BI tooling and reporting data models