About The Opportunity :

Join an engineering-focused team building scalable, production-grade data platforms on Google Cloud.

You will design, implement, and operate end-to-end data pipelines that power analytics, reporting, and ML use cases optimising for cost, performance, and reliability.

Role & Responsibilities :

- Design, build, and maintain scalable ETL/ELT pipelines on GCP (ingest, transform, publish) using Cloud Dataflow, BigQuery, and Pub/Sub.

- Implement data modelling and data warehouse solutions in BigQuery to support analytics and BI workloads.

- Author reusable infrastructure as code for data platforms using Terraform and manage deployments across environments.

- Develop Python-based data processing jobs and optimise SQL for performance and cost in large-scale datasets.

- Troubleshoot pipeline failures, implement monitoring and alerting, and drive SLO/SLA improvements for data products.

- Collaborate with data consumers, analytics, and ML teams to translate requirements into robust, observable data solutions.

Skills & Qualifications :

Must-Have :

- Google BigQuery.

- Cloud Dataflow.

- Cloud Pub/Sub.

- Python.

- SQL.

- Terraform.

Preferred :

- Apache Beam.

- Apache Airflow.

- Kubernetes.

Qualifications & Other Requirements :

- Proven hands-on delivery building data pipelines and data warehouses on Google Cloud.

- Ability to work on-site in India and collaborate closely with cross-functional teams.

- Strong focus on engineering best practices: testing, CI/CD, observability and cost optimisation.

Benefits & Culture Highlights :

- Opportunity to shape cloud data architecture and work on high-impact enterprise analytics projects.

- Collaborative, technically driven environment with mentorship and scope for skill growth.

- Competitive compensation and career progression for high-performing engineers.