Job Overview :

We are seeking a highly experienced Senior Data Engineer to design, develop, and optimize scalable data pipelines in a cloud-based environment.

The ideal candidate will have deep expertise in PySpark, SQL, Azure Databricks, and experience with either AWS or GCP.

A strong foundation in data warehousing, ELT/ETL processes, and dimensional modeling (Kimball/star schema) is essential for this role.

Key Requirements :

- Strong proficiency in PySpark and SQL for data transformation and pipeline development.

- Experience working in Azure Databricks or equivalent Spark-based cloud platforms.

- Practical knowledge of cloud data environments - Azure, AWS, or GCP.

- Solid understanding of data warehousing concepts, including Kimball methodology and star/snowflake schema design.

- Proven experience designing and maintaining ETL/ELT pipelines in production.

- Familiarity with version control (e.g., Git), CI/CD practices, and data pipeline orchestration tools (e.g., Airflow, Azure Data Factory).

- Experience in the financial domain or understanding of investment banking workflows.

Total Experience : 7 to 9 years.