Senior Data Engineer (Azure Databricks)

Senior Databricks Engineer Job Summary: Seeking a Senior Databricks Engineer with strong experience in Databricks, Apache Spark, Delta Lake, and cloud data engineering. The candidate will design, develop, optimize, and maintain scalable data pipelines supporting analytics and AI-driven healthcare applications. Responsibilities: Design and develop scalable data engineering solutions using Databricks and Apache Spark. Build and optimize ETLELT pipelines using PySpark, Python, or Scala. Implement D

Key Responsibilities Pipeline Development Design, implement, and optimize scalable ETL/ELT pipelines using Databricks (PySpark, SQL, Delta Lake) to ingest structured and semi structured data from multiple sources (APIs, databases, streaming). Data Warehousing Build and maintain cloud data warehouse solutions (Snowflake / Azure Synapse) design star schemas, fact/dimension tables, and aggregate tables for high performance reporting. Data Modeling Create logical and physical data models for

job summary: The Senior Data Engineer will design, build, and maintain the scalable data pipelines, models, and infrastructure that power analytics, business intelligence, and machine learning products across the company. Partnering closely with business, product, and analytics teams, you will translate complex requirements into elegant, reliable data solutions and help drive the delivery of innovative data products. This role reports to the Senior Manager, Data Engineering. Build E2E Azure Dat

The Data Engineering Manager will lead a scrum team of data engineers in the design, development, and delivery of Sidley's enterprise Databricks data platform. This role blends hands-on technical leadership with people management, balancing day-to-day engineering execution with longer-term architectural direction. Partnering closely with the Data Architect, analytics, and business teams, the Data Engineering Manager will set technical standards, drive data quality, and ensure the team delivers s