Key Responsibilities:

- Design, develop, and maintain scalable data pipelines and ETL processes.

- Build data pipelines using GCP Dataflow and integrate them with Cloud Composer, Apache Airflow, or other scheduling tools.

- Develop and optimize data solutions using Google BigQuery.

- Work with relational databases including Oracle, PostgreSQL, and Spanner.

- Develop solutions for both structured and unstructured data.

- Implement ETL workflows for data extraction, transformation, and loading.

- Work on bulk data loads and streaming data integration.

- Apply data modeling and data architecture principles to develop scalable solutions.

- Implement and maintain CI/CD pipelines using tools such as Jenkins, GitHub Actions, Maven, and Gradle.

- Monitor, troubleshoot, and optimize data pipelines and processing jobs.

- Collaborate with data engineers, architects, application teams, and business stakeholders.

- Contribute to data modernization and cloud transformation initiatives.

- Follow engineering best practices for code quality, version control, testing, and deployment.

Required Skills & Experience:

- 5 - 12 years of overall experience, with 4 - 6 years of relevant Data Engineering and ETL experience.

- Strong hands-on experience building data pipelines using GCP Dataflow.

- Experience with Cloud Composer / Apache Airflow or similar scheduling/orchestration tools.

- Strong hands-on experience with BigQuery.

- Experience with relational databases such as Oracle, PostgreSQL, or Google Cloud Spanner.

- Good understanding of OLTP, Data Warehousing, Data Modeling, Data Architecture principles, and ETL processes.

- Experience handling structured and unstructured data.

- Strong understanding of GCP Data Engineering concepts.

- Experience with CI/CD tools such as Jenkins, GitHub Actions, Maven, and Gradle.

Good to Have:

- Experience with bulk data loads and streaming data integration.

- Exposure to replication technologies such as GoldenGate, SharePlex, StreamSets, and Striim.

- Experience with large-scale cloud data migration or modernization projects.

Candidate Profile:

- Strong analytical and problem-solving skills.

- Ability to design scalable and reliable data engineering solutions.

- Good understanding of cloud data engineering best practices.

- Strong communication and collaboration skills.

- Ability to work effectively in a fast-paced, cross-functional environment.