Data Engineer III - Analytics Engineer (Databricks)

As an Analytics Engineer Senior Associate at JPMorgan Chase within the RM&C Data Analytics & Intelligent Automation team, you will support our analytics engineering roadmap to enable cloud-native BI and analytics. You will work across the Lakehouse stack, consuming data products, building integration pipelines, and producing high-impact dashboards and self-service analytics products that business teams trust and use.

• Develop end-to-end pipelines on Databricks using DLT, Delta Lake, and Unity Catalog for governance, lineage, and access controls.
• Build ingestion/integration pipelines in Python/PySpark, consuming JPMC’s data products into the Lakehouse.
• Implement a governed self-service layer in Databricks SQL with curated semantic models and intuitive views.
• Ensure proper data governance in partnership with data product owners and data architects.
• Communicate clearly with non-technical stakeholders and turn data into actionable narratives.
• Deliver executive-ready dashboards and self-service analytics in Tableau and/or Sigma on Databricks-served data.

• Degree or certification in Computer Science, Information Systems, Data Engineering, or a related discipline.
• 5+ years of applied experience in data engineering, analytics engineering, or business intelligence in a complex, regulated environment.
• Hands-on ability to design, write, test, and maintain ETL pipelines independently, with strong SQL fluency and production-grade Python, PySpark experience.
• Strong communication skills and a customer-centric mindset, with the ability to engage business users.
• Experience with Databricks, including building and executing pipelines on the platform.
• Experience with self-service analytics platforms, semantic layers, and BI data models.
• Comfort operating in a controlled environment with working knowledge of Git, Jules, and ServiceNow.