Role Description

Experience: 5 to 8 years. We are seeking a highly experienced Senior Data Engineer to design, develop, and optimize scalable data pipelines in a cloud-based setting. 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. 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

Skills

PySpark, SQL, Databricks, Cloud Data Warehousing, AWS, CI/CD, Git, Azure Data Factory, Microsoft Azure

📌 Lead II - Data Engineering (Pune)
🏢 UST
📍 Pune