Sr Data Engineer

We are seeking a high-caliber Data Engineer with 3 5 years of experience to join our Data Platform team. You will be responsible for building and maintaining a unified "Lakehouse" architecture. The ideal candidate is an expert in Snowflake for high-concurrency warehousing and Databricks for complex, large-scale data processing and engineering.

• Pipeline Architecture: Design and implement end-to-end ELT/ETL pipelines using the Medallion Architecture (Bronze/Silver/Gold) across Databricks and Snowflake.

• Processing Mastery: Use PySpark and Databricks SQL for heavy-lift data engineering, cleansing, and unstructured data processing.

• Warehouse Optimization: Architect and manage Snowflake environments, including virtual warehouses, clustering keys, and materialized views for sub-second query performance.

• Data Governance: Implement security and governance frameworks using Unity Catalog (Databricks) and Role-Based Access Control (Snowflake).

• Integration & Orchestration: Synchronize data between Delta Lake and Snowflake using tools like Snowpipe, dbt, or Airflow.

• Cost Management: Monitor and optimize credit consumption in both platforms to ensure architectural efficiency.

• Experience: 3 5 years in a Data Engineering role with a focus on cloud-native stacks (AWS, Azure, or GCP).

• Databricks Skills: Deep proficiency in Spark (Python/Scala), Delta Lake, and experience with Delta Live Tables (DLT).

• Snowflake Skills: Expert knowledge of Snowpark, Streams & Tasks, Zero-Copy Cloning, and Data Sharing.

• SQL: Advanced mastery of analytical SQL (window functions, complex joins, and recursive CTEs).

• Tooling: Hands-on experience with dbt (Data Build Tool) and version control via Git.