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We are looking for an experienced Databricks Developer to design, develop, and optimize scalable data engineering solutions using the Databricks platform. The candidate should have strong expertise in Apache Spark, PySpark/SQL, Delta Lake, data pipelines, and cloud data platforms.

Key Responsibilities:

- Develop and maintain scalable data pipelines using Databricks and Apache Spark.
- Build batch and streaming data processing solutions using PySpark and SQL.
- Design and implement Delta Lake / Lakehouse architecture.
- Develop ETL/ELT workflows for structured and unstructured data.
- Optimize Spark jobs, queries, clusters, and data pipelines for performance and cost.
- Integrate Databricks with cloud storage, databases, APIs, and enterprise data platforms.
- Implement data quality, validation, reconciliation, and monitoring processes.
- Work with data architects and data engineers to implement scalable data solutions.




- Support CI/CD and automated deployment of Databricks notebooks and workflows.
- Troubleshoot production data pipelines and resolve performance or data-quality issues.
- Follow data governance, security, and engineering best practices.

Required Skills:

- 6-11 years of experience in Data Engineering.
- Solid hands-on experience with Databricks and Apache Spark.
- Strong knowledge of PySpark and SQL.
- Experience with Delta Lake and Lakehouse architecture.
- Experience building enterprise-grade ETL/ELT pipelines.
- Strong understanding of data warehousing and data modelling.
- Experience with AWS, Azure, or GCP data platforms.
- Exposure to Databricks Workflows, Unity Catalog, MLflow, and Delta Live Tables is preferred.
- Experience with Git, CI/CD, and DevOps practices is an advantage.

📌 Databricks Developer - PySpark (India)
🏢 Mukul Consultants India
📍 India