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