Data and Analytics Engineer

Job Title : DBT Developer Experience- 5 + Years
Location: Remote

Key Responsibilities

• DBT Development & Modeling: Design, develop, test, and deploy production-grade, secure, and performant data models using dbt (Jinja and SQL) in a modular and incremental fashion.
• Databricks Integration: Utilize dbt to transform data residing in Databricks Unity Catalog and Delta Lake tables, ensuring models are optimized for consumption by Snowflake and other downstream systems.
• Performance Optimization: Optimize dbt models and associated Databricks queries (SQL/Spark) for scale, efficiency, and cost, leveraging partitioning, clustering, and table optimization techniques (e.g., Z-Ordering).
• Code Quality & Governance: Establish and enforce best practices for dbt development, including documentation, version control (GitLab/Git), code reviews, and comprehensive testing (data quality, uniqueness, referential integrity).
• CI/CD Integration: Integrate dbt projects into the CI/CD pipeline (managed via GitLab) for automated testing and deployment across development, staging, and production environments.
• Data Governance: Work closely with Data Governance and Compliance teams to ensure models handle sensitive data (e.g., OneTrust consent data)

• Minimum 5+ years of professional experience in Data Engineering, Business Intelligence, or Analytics Engineering.
• 2+ years of hands-on, production experience with dbt (data build tool).
• Expert proficiency in SQL and experience with complex data modeling techniques (e.g., dimensional modeling).
• Proven experience with Databricks/Spark environment, specifically reading from Delta Lake tables and utilizing Databricks SQL or standard Spark SQL for transformations.
• Demonstrable experience working with data specific to the Pharmaceutical or Life Sciences industry, including understanding of systems like Veeva CRM, HCP/HCO, Address & Affiliation data, Sales & Interactions data.
• Experience with CI/CD practices and tooling (e.g., GitLab, GitHub Actions) for automated code deployment.
• Familiarity with Cloud Data Warehouses, preferably Snowflake or similar platforms.