About The Opportunity
A fast-scaling tech consultancy operating at the intersection of cloud infrastructure and enterprise data modernization, we empower Fortune 500 and mid-market clients across India to build scalable, secure, and intelligent data ecosystems on Google Cloud Platform. Our data engineers architect and deploy cloud-native data pipelines, Lakehouse architectures, and real-time analytics engines that drive AI/ML adoption, regulatory compliance, and operational efficiency for customers in BFSI, healthcare, retail, and logistics sectors.
Role & Responsibilities
- Design and implement scalable data ingestion, transformation, and orchestration pipelines on GCP using Pub/Sub, Dataflow, BigQuery, and Composer.
- Build and maintain data lake and warehouse architectures using BigQuery, Cloud Storage, and Dataproc with partitioning, clustering, and cost-optimization strategies.
- Automate ETL/ELT workflows using Apache Airflow (Composer) and schedule, monitor, and alert on pipeline health using Cloud Monitoring and Logging.
- Optimize query performance and reduce compute costs through materialized views, partition pruning, and BigQuery reservation management.
- Enforce data governance, lineage, and quality checks using Data Catalog, Dataplex, and custom validation frameworks.
- Collaborate with data scientists and analysts to surface curated datasets for ML training and BI dashboards, ensuring low-latency access and schema reliability.
Skills & Qualifications
Must-Have
- BigQuery
- Dataflow
- Pub/Sub
- Cloud Composer
- Cloud Storage
- Apache Airflow
- SQL
- Python
Preferred
- Dataplex
- Looker Studio
- Pub/Sub streaming pipelines
Benefits & Culture Highlights
- Work alongside GCP-certified architects and data leaders on high-impact enterprise projects across verticals.
- Access to GCP certification reimbursements, hands-on labs, and cloud sandbox environments for skill growth.
- On-site collaborative culture with flexible work hours, performance bonuses, and rapid career progression based on impact.
Skills: data,gcp,cloud,pipelines
