About the role
- Design and implement scalable data architectures on Google Cloud Platform
- Build and optimize high-performance data pipelines using BigQuery
- Develop robust ETL/ELT frameworks and reusable components
- Optimize BigQuery performance (partitioning, clustering, cost optimization)
- Lead data modeling (dimensional modeling, star/snowflake schemas)
- Ensure data governance, security, and compliance
- Integrate data from multiple sources (APIs, streaming, batch systems)
- Mentor junior engineers and guide best practices
- Work closely with stakeholders across analytics, BI, and AI teams
- Strong hands-on experience with Google Cloud Platform (GCP ecosystem)
- Deep expertise in BigQuery (query optimization, architecture design)
- Advanced SQL and data modeling skills
- Strong experience in Python/Scala for data engineering
- Experience with orchestration tools like Apache Airflow
- Hands-on experience with GCP services like:Dataflow
Pub/Sub
Cloud Storage
Dataproc
- Experience with streaming pipelines (real-time data processing)
- Knowledge of data governance frameworks
- Exposure to ML pipelines or AI platforms
- Experience in BFSI domain (preferred)
- Familiarity with tools like dbt
- Drive architectural decisions
- Define data engineering standards and best practices
- Mentor and upskill team members
- Ensure scalability, reliability, and cost efficiency of solutions
- Strong ownership mindset
- Ability to handle complex data challenges
- Excellent communication with business and technical teams
- Experience in enterprise-scale delivery