Responsibilities-

- Develop, maintain, and optimize ETL/ELT pipelines using Databricks, PySpark, and SQL.
- Create, schedule, monitor, and troubleshoot Databricks Jobs, Workflows, and Pipelines.
- Design and implement scalable data processing solutions for large datasets.
- Perform data cleansing, transformation, validation, and quality checks.
- Collaborate with business and analytics teams to understand requirements and deliver data solutions.
- Support production deployments, monitoring, and issue resolution.
- Follow best practices for code versioning, documentation, and performance optimization.

Educational Qualifications

- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.

Competencies Required:

- 2–3 years of experience in Data Engineering.




- Solid proficiency in SQL and PySpark.
- Hands-on experience with Azure Databricks.
- Experience in creating and managing Databricks Jobs, Workflows, and Pipelines.
- Good understanding of ETL/ELT processes and data warehousing concepts.
- Familiarity with Git/version control and basic CI/CD practices.
- Strong analytical and problem-solving skills.

Experience -

- Experience with Azure Data Factory (ADF), ADLS, Synapse, or other Azure services.
- Exposure to Delta Lake and Lakehouse architecture.
- Knowledge of performance tuning and optimization of Spark workloads.

📌 Associate Data Engineer (Mumbai)
🏢 ICICI Lombard
📍 Mumbai