ETL Data / Platform Engineer

Experience: 4–8 Years

Job Summary

We are looking for an experienced ETL Data / Platform Engineer with strong 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.
• Strong hands-on experience with Databricks – Mandatory.
• Good experience in PySpark, Python, and SQL.
• Strong 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.