Data Platforms Senior Engineer – Databricks
Waters Corporation (company site, opens in a new tab)4–7 yrsBengaluruOn-siteDirect career pageEst. 14–28 LPA
Posted on 15 Sept
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Job description
Structured overview of role & requirements
About This Role
- Lead design and development of scalable ETL pipelines for the Enterprise Data Lakehouse using Databricks, PySpark, SQL, and Python.
- Develop, optimize, and maintain data pipelines and processing solutions including incremental data processing and performance improvements.
- Manage source code and implement CI/CD pipelines using GitHub, ensuring efficient version control and deployment workflows.
Minimum Requirements
- Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related field.
- 4-7 years of relevant experience in Data Engineering, ETL, Data Warehousing, or data analytics decision support roles.
- Strong hands-on experience with Databricks platform, PySpark, Python, SQL, and ETL tools like SSIS and Azure Data Factory.
- Experience with version control systems (Git) and CI/CD pipeline implementation; knowledge of data warehousing concepts and Big Data technologies (Spark, Hadoop, Kafka).
Ideal Candidate Profile
- Experienced in managing end-to-end data pipeline development in cloud-based environments, particularly using Azure Databricks.
- Technically proficient in both development and operational aspects including source code management, performance tuning, and CI/CD.
- Skilled at translating business requirements into scalable technical solutions following standard data engineering practices and methodologies.