Sr Data Engineer-GCP
Summary
Senior Data Engineer who designs, builds, and maintains scalable data pipelines on GCP for enterprise data migration, validation, reconciliation, and modernization projects. Core stack: Python, PySpark, SQL, and GCP services like BigQuery, Dataflow, Dataproc, and Cloud Composer.
We are looking for a hands‑on Senior Data Engineer with strong experience in data engineering and migration projects. The role will focus on building scalable data pipelines preferably GCP, data migration, reconciliation, validation, and modernization of enterprise data workloads.
Key Responsibilities
- Design, develop, and maintain data pipelines using Python, PySpark, and SQL.
- Work on data migration and modernization initiatives on GCP.
- Develop ETL/ELT pipelines for ingesting, transforming, and processing large datasets.
- Implement data validation, reconciliation, matching, and data quality frameworks.
- Apply rule-based and ML-assisted approaches for data validation and matching where applicable.
- Optimize data processing workloads and troubleshoot pipeline and data quality issues.
- Work with GCP services and modern data platforms to build reliable production-grade solutions.
- Collaborate with architects, analysts, and client teams on technical design and delivery.
Mandatory Skills
- 6–8 years of hands‑on data engineering experience.
- Strong hands‑on expertise in Python, PySpark, and SQL.
- Strong experience with cloud based data engineering preferably GCP
- Experience with services such as GCP services BigQuery, Cloud Storage, Dataflow, Dataproc, or Cloud Composer.
- Strong understanding of ETL/ELT, data migration, data modeling, and data warehousing.
- Experience building and supporting production‑grade data pipelines.
- Experience with data validation, reconciliation, matching, and data quality.
- Good understanding of Git, CI/CD, monitoring, and production support.
Preferred Skills
- Experience with Snowflake or Databricks in migration or integration scenarios.
- Exposure to ML-based data matching, anomaly detection, or automated data validation.
- Experience with large-scale cloud migration or data platform modernization programs.
- Exposure to Airflow/Cloud Composer and orchestration frameworks.
- Experience working in an IT services/client delivery environment.