About the role
As a Senior Data Engineer, you will design, build, and evolve scalable data products, pipelines, and data architectures on Google Cloud Platform (GCP).
The role is strongly focused on GCP and requires hands-on experience building reliable data solutions that support analytics, reporting, machine learning, and business decision-making. You will also help establish engineering standards, improve data quality and governance, and work closely with technical and business stakeholders.
Key Responsibilities
1) Data Engineering & Architecture
Design and evolve scalable data architectures on GCP.
Build and maintain reliable end-to-end data pipelines.
Develop and optimize data solutions using BigQuery, Dataflow, Cloud Run, Composer, and GCS.
Build reusable and well-structured data products for analytics and reporting.
Translate business requirements into scalable technical solutions.
Support integrations with enterprise platforms, APIs, SAP, and other data sources.
2) Data Transformation & Modeling
Develop transformation workflows using SQL, Python, and dbt.
Build and maintain reusable data models and semantic layers.
Establish standards for modeling, testing, documentation, and deployment.
Ensure datasets are analytics-ready and reusable across teams.
3) Data Quality, Governance & Reliability
Implement data quality controls, validation, reconciliation, and automated testing.
Ensure data remains accurate, secure, governed, and accessible.
Monitor pipeline health, freshness, performance, and operational stability.
Troubleshoot production issues and drive long-term improvements.
Contribute to governance standards around access, naming, lineage, and lifecycle management.
4) Platform Ownership & Engineering Standards
Contribute to infrastructure and deployment standards using Terraform, Docker, CI/CD, and Git.
Support secure access management and appropriate data permissions.
Promote engineering best practices around testing, code quality, documentation, and version control.
Mentor colleagues and support knowledge sharing within the team.
5) Collaboration & Communication
Work closely with Product Owners, Analysts, Data Scientists, Engineers, and business stakeholders.
Translate business requirements into practical technical solutions.
Communicate technical designs, risks, trade-offs, and progress clearly.
Take end-to-end ownership from requirements through production support.
Nice-to-Have
Perks & Benefits
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