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Job Description: Role: Senior Databricks Developer The Databricks Data Engineer will be responsible for designing, building, and optimizing scalable data pipelines and lakehouse solutions using Databricks. The role requires strong handson experience in data engineering, distributed data processing. Location: Gurgaon/Bangalore (5 days mandatory work from office) Type: Full-time Experience: 9+ years Key Responsibilities Design, build, and maintain ETL/ELT pipelines on Databricks using PySpark, Spark SQL, and Delta Lake. Develop and optimize data ingestion frameworks, data transformations, and endtoend workflows for batch and streaming use cases. Implement Delta Lakebased architectures, including versioning, schema evolution, and ACIDcompliant pipelines. Work with stakeholders to understand data requirements and translate them into scalable data engineering solutions. Manage and optimize Databricks clusters, jobs, and notebooks for performance and cost efficiency. Ensure data quality, reliability, and observability through validation frameworks and monitoring. Contribute to data modeling, metadata management, and best practices within the data platform. Must have Skills & Experience 5+ years of experience in data engineering with 3+ years of hands on expertise in Databricks. Handson experience with Spark (PySpark/Spark SQL) and distributed data processing. Solid SQL knowledge and experience working with large-scale datasets Strong understanding of Delta Lake, medallion architecture, and scalable lakehouse patterns. Good understanding of CI/CD, Git, and modern DevOps practices for data pipelines. Familiarity with structured/unstructured data, data quality frameworks, and performance tuning. Responsibilities: Key Responsibilities Design, build, and maintain ETL/ELT pipelines on Databricks using PySpark, Spark SQL, and Delta Lake. Develop and optimize data ingestion frameworks, data transformations, and endtoend workflows for batch and streaming use cases. Implement Delta Lakebased architectures, including versioning, schema evolution, and ACIDcompliant pipelines. Work with stakeholders to understand data requirements and translate them into scalable data engineering solutions. Manage and optimize Databricks clusters, jobs, and notebooks for performance and cost efficiency. Ensure data quality, reliability, and observability through validation frameworks and monitoring. Contribute to data modeling, metadata management, and best practices within the data platform. Qualifications: 5+ years of experience in data engineering with 3+ years of hands on expertise in Databricks. .
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Most developer ads you'll see are written in English: 18,397 of the 24,795. That doesn't tell you whether the job itself requires you to speak English or work in English daily, so read each posting carefully. Don't assume the language of the ad matches the language of the team.
The employers posting the most developer roles are Link Group (369 jobs), Upvanta (257), jobgether (226), and OfferZen (212). If you're applying to any of these, research their hiring patterns. They move fast and post often, which means they're either scaling hard or replacing people who didn't fit.
In your interview, expect this: 'Walk me through the last time you had to debug something that took you more than an hour. What was it, what did you try first, and what would you do differently?' Hiring managers ask this to see if you think systematically or just try random fixes. Have a real example ready with specifics.