Sr Data Engineer, Python + Spark (Data Federation skillset - Data Lakehouse - Eg: Starburst) - New York

As a Senior Data Engineer , you will be responsible for breaking down data silos.

This role focuses on building a unified, high-performance data layer using Data Federation techniques.

You won't just move data; you will architect a Data Lakehouse environment where disparate sources feel like a single, cohesive database for our analytics and AI teams.

• Data Federation Architecture: Design and implement federated query layers (e.g., Starburst/Trino ) to allow high-speed analytics across distributed data sources without unnecessary data movement.
• ETL/ELT Pipeline Development: Build scalable, distributed data processing pipelines using Python and Apache Spark (PySpark).
• Lakehouse Implementation: Manage and optimize modern table formats like Delta Lake , Apache Iceberg , or Hudi to bring ACID transactions to our data lake.
• Performance Tuning: Optimize Spark jobs and SQL queries across the federation layer to minimize latency and manage compute costs.
• Governance & Security: Implement fine-grained access control and data masking within the federation engine to ensure data privacy across all connected platforms.

• Python & Spark: 5+ years of experience with Python and deep expertise in Apache Spark tuning (partitioning, shuffling, caching).
• Data Federation Tools: Hands-on experience with Starburst Enterprise , Trino (Presto) , or Dremio .
• Lakehouse Ecosystem: Proven track record working with Delta Lake or Iceberg architectures.
• Cloud Platforms: Extensive experience with AWS (EMR, S3, Glue) , Azure (Databricks, ADLS) , or GCP .
• SQL Mastery: Expert-level SQL skills for complex analytical queries and query plan analysis.
• Data Modeling: Proficiency in designing Star/Snowflake schemas and understanding "Medallion Architecture" (Bronze, Silver, Gold layers).