Job Description:

Key Responsibilities:

- Design, develop, and maintain scalable ETL/ELT pipelines using Python, SQL, and Java on Google Cloud Platform (BigQuery, Dataflow, Composer).

- Lead migration of legacy on-premise data warehouses and BI datasets to cloud-native architectures.

- Build reliable, high-performance data models and data pipelines to support enterprise analytics and financial reporting.

- Monitor, troubleshoot, and optimize production data pipelines and ingestion processes.

- Collaborate with Finance, Analytics, Supply Chain, and global business teams to deliver scalable data solutions.

- Implement data quality, validation, reconciliation, monitoring, and governance frameworks.

- Drive engineering excellence through CI/CD, automation, reusable frameworks, and cloud best practices.

- Develop dashboards and reporting solutions using Looker/Looker Studio and semantic models (LookML).

- Mentor junior engineers and contribute to technical capability building within the team.

Required Skills:

- 7+ years of experience in Data Engineering/Data Warehousing.

- 3+ years of hands-on experience with Google Cloud Platform (GCP).

- Strong expertise in SQL, Python, and Java.

- Experience with BigQuery, Dataflow, Composer, ETL/ELT pipeline development, and cloud migration.

- Strong knowledge of data modeling, data governance, metadata management, and data quality frameworks.

- Hands-on experience with Looker/Looker Studio and LookML.

- Experience with CI/CD, Git, and deployment automation.