We are looking for an experienced ETL Data / Platform Engineer with solid hands-on experience in Databricks to build and maintain scalable data pipelines and data platforms.
Key Responsibilities
Develop and maintain ETL/ELT data pipelines using Databricks.
Work with PySpark, Python, and SQL for data processing and transformation.
Integrate data from multiple sources into data lakes and data warehouses.
Develop, optimize, and monitor data pipelines.
Implement data quality checks, error handling, and performance optimization.
Work with cloud platforms such as Azure, AWS, or GCP.
Collaborate with data engineers, architects, and business teams.
Follow Git, CI/CD, and deployment best practices.
Mandatory Skills
4–8 years of experience in Data Engineering / ETL.
Solid hands-on experience with Databricks – Mandatory.
Good experience in PySpark, Python, and SQL.
Solid knowledge of ETL/ELT concepts and data pipelines.
Experience with Data Lake / Data Warehouse.
Experience with Azure, AWS, or GCP.
Good understanding of data integration, data modeling, and data quality.
Good to Have
Experience with Azure Data Factory / AWS Glue.
Knowledge of Delta Lake.
Experience with Apache Spark / Kafka.
Experience with Airflow.
Knowledge of CI/CD and DevOps.