Tech Stack

Description

Design, build, and maintain high-performance data platforms using Snowflake and Azure Databricks for enterprise clients. Act as a trusted advisor to ensure scalable, secure, and cost-optimized data ecosystems.

Requirements

• 5+ years in Data Engineering, with at least 3 years in both Snowflake and Databricks.
• Experience supporting external customers with strict SLAs and complex governance.
• Advanced SQL and Python skills.
• Experience with Snowflake: Snowpipe, Streams Tasks, Dynamic Tables, Zero-Copy Cloning, Snowpark, Data Sharing.
• Experience with Azure Databricks: Spark SQL, PySpark, Delta Lake, Unity Catalog, Medallion Architecture.
• Experience with Azure Data Factory, Airflow, or dbt.
• Experience with Azure Data Lake Storage, Azure DevOps, and Terraform/Bicep.

Responsibilities

• Design and implement end-to-end data lakehouse architectures using Azure Databricks, Azure HDInsights, and Snowflake.
• Build scalable, metadata-driven ETL/ELT pipelines using Azure Data Factory, PySpark, and SnowSQL.
• Provide Tier-3 technical support for client environments, including performance tuning and architectural optimizations.
• Oversee data movement and integration strategies across Azure, AWS, and GCP.
• Monitor and optimize Snowflake credit consumption and Databricks cluster usage.
• Implement enterprise-grade security including RBAC, Row-Level Security, and data masking.