- Design and develop RESTful APIs and backend services using Python (FastAPI / Flask / Django) (Must).

- Build, orchestrate, and optimize data pipelines using Databricks, PySpark, and Delta Lake(Good).

- Integrate backend systems with data lakes, data warehouses, and external APIs.

- Work closely with data engineers, analysts, and ML teams to enable efficient data access and transformation.

- Ensure best practices in code quality, version control (Git), testing, and CI/CD.

- Optimize Databricks jobs for performance and cost efficiency.

- Troubleshoot and monitor production workloads using logging and alerting tools.

Requirements:

- Strong proficiency in Python (OOPs, multithreading, error handling, performance tuning).

- Hands-on experience with Databricks (Notebook development, job scheduling, cluster management).

- Strong understanding of PySpark for distributed data processing.

- Experience with SQL and working knowledge of data lakes and Delta Tables.

- Familiarity with cloud platforms (Azure / AWS), especially services like S3 Lambda, EventHub, ADLS, Glue, or Synapse.

- Experience in API development and integrating with third-party systems.

- Knowledge of CI/CD pipelines (Azure DevOps / GitHub Actions / Jenkins).

- (Good to have).

- Solid understanding of data modeling, schema design, and data cataloging (Athena / Unity Catalog).

Good To Have:

- Familiarity with containerization (Docker / Kubernetes).

- Exposure to ML model integration or feature engineering pipelines.

- Experience with Databricks REST APIs or job automation using Databricks CLI.