GCP Data engineer

Job Summary:

We are seeking a Senior Data Engineer to join a Global Data Analytics & Insights team focused on transforming enterprise data management and democratizing access to insights. This role will lead a large-scale data migration from external agency-managed environments into an internal Google Cloud Platform (GCP) ecosystem. You will drive discovery, define and execute migration strategy, rebuild ingestion pipelines, and ensure secure, compliant, always-on access for internal teams and approved external partners. The work directly supports global analytics initiatives by delivering scalable, high-quality, governed data products

Roles and Responsibility

• Lead discovery and deep analysis of existing third-party data warehouses (e.g., Snowflake or hybrid setups), including data assets, lineage, dependencies, and integration patterns.
• Define and execute end-to-end migration strategy to move data assets and workflows into internal GCP environments.
• Handle and migrate third-party API-based ingestion flows so inbound data lands in GCP data lakes/warehouses.
• Partner with product lines, business stakeholders, and downstream consumers (dashboards, CRM, analytics) to capture requirements and ensure smooth data consumption.
• Design, build, and maintain scalable ingestion and transformation pipelines using Python, SQL, PySpark, and DBT/Dataform.
• Develop and manage GCP-native data solutions using BigQuery, Dataflow, Pub/Sub, Cloud Functions, Cloud Run, Dataproc, etc.
• Implement strong data governance, security, access controls, and compliance practices using GCP security capabilities.
• Integrate DevSecOps quality and security checks (e.g., SonarQube, FOSSA) into CI/CD pipelines, and respond to findings.
• Orchestrate workflows with Apache Airflow/Astronomer and provision infrastructure via Terraform (IaC best practices).
• Monitor and optimize performance, scalability, reliability, and cost-efficiency of pipelines and storage.
• Promote engineering best practices, reusable patterns, automation, and continuous improvement across teams.
• Produce clear documentation and communicate technical decisions effectively to technical and non-technical audiences.

Required Skills:

• Expert proficiency in Python (NumPy, Pandas), SQL, and PySpark.
• Strong production-grade GCP experience with BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Functions, Cloud Run, Data Fusion/Data Prep.
• Proven ability to build scalable ELT/ETL ingestion and curation pipelines.
• Hands-on experience with DBT and/or Dataform for transformations.
• Workflow orchestration expertise with Apache Airflow and/or Astronomer.
• Proven experience integrating and managing third-party APIs for data ingestion.
• CI/CD and DevOps exposure (e.g., Tekton) and strong GitHub-based version control.
• Infrastructure as Code with Terraform.
• Solid knowledge of data governance, encryption, masking, access management, and cloud security best practices.
• Strong understanding of modern data ecosystems: data warehouses/lakes, metadata, meshes/fabrics, and analytics/AI use cases.
• Experience with Agile delivery, user stories, and cross-functional collaboration.
• Willingness to work from office (Chennai location).

Preferred Skills:

• Direct experience with Snowflake migration, exploration, and optimization.
• Experience with Java.
• Familiarity with Master Data Management (MDM) concepts/tools.
• Exposure to additional security/performance tools (e.g., Checkmarx, Dynatrace).
• Working knowledge of GDPR and data privacy impact on architecture.

Required Experience:

• 5–7 years in Data Engineering or Software Engineering with data-intensive systems.
• 2+ years building and deploying production-scale cloud data platforms on GCP.
• Demonstrated leadership in delivering migration or large data engineering programs.
• Strong track record of optimizing compute/storage cost and performance in cloud environments.

Education:

• Bachelor's degree in Computer Science, Information Technology, Data Analytics, or related field (or equivalent practical experience).