Description

Job Summary:
We are seeking a Senior Data Engineer with 10+ years of experience and strong production-level expertise in Databricks and Snowflake. The candidate will design and develop scalable data pipelines, cloud data warehouse solutions, and data models for enterprise analytics.

Key Responsibilities

• Design and optimize ETL/ELT pipelines using Databricks, PySpark, Python, SQL, and Delta Lake.
• Develop and maintain Snowflake/Azure Synapse data warehouse solutions, including fact/dimension tables and star schemas.
• Build logical and physical data models and implement SCD Type 2 and dimensional modeling.
• Optimize Spark jobs, SQL queries, partitioning, and large-scale data processing.
• Implement data quality, governance, monitoring, and lineage using Great Expectations/Unity Catalog.
• Develop workflows using Airflow, Azure Data Factory, or Prefect.
• Implement CI/CD using Azure DevOps/GitHub Actions, Git, and Terraform.
• Collaborate with architects, analysts, product managers, and engineering teams to deliver scalable data solutions.

Required Skills

• 10+ years of Data Engineering experience.
• Mandatory: Strong production experience with Databricks and Snowflake.
• Expert Python, SQL, PySpark, and Apache Spark.
• Strong experience with Delta Lake, Unity Catalog, ETL/ELT, and Data Modeling.
• Experience with SCD Type 2, dimensional modeling, and cloud data warehousing.
• Experience with Airflow/Azure Data Factory/Prefect.
• Strong Git and CI/CD experience.

Preferred

• Kafka, Event Hubs, or Kinesis.
• dbt, Terraform, Power BI/Tableau/Looker.
• Data Mesh/Data Fabric.
• Databricks certification or MLflow/MLOps experience.

Education: Bachelor's/Master's degree in Computer Science, Information Systems, Engineering, or related field

Key Skills

Education

Any Graduate