Why Join Us
We are building next-generation data engineering and data analytics business data infrastructure. If you enjoy turning complex business data into actionable insights and delivering end-to-end systems, this role is for you.
Key Responsibilities
About The Role
You will own, build, and maintain our business data pipeline and enrichment system on top of Snowflake. This system powers enterprise level analytics, detections, and intelligence. A core part of your job will be to design and implement new components, improve reliability and performance, and ensure data quality and observability.
Your Impact & Responsibilities
- Lead, design, and maintain scalable Snowflake ELT pipelines, ensuring reliability, performance, and adherence to best practices.
- Architect endtoend data solutions including ingestion, transformation, orchestration, deployment, monitoring, and continuous optimization.
- Oversee SQL, Python, and Snowflake-based development, ensuring high code quality, modularity, and automation readiness.
- Manage Git-based workflows (branching, pull requests, code reviews) and enforce CI/CD processes for seamless data pipeline releases.
- Proactively monitor and optimize Snowflake performance, clustering, compute usage, and cost efficiency.
- Collaborate with cross-functional teams to translate data requirements into robust Snowflake models and automated ELT frameworks.
- Mentor and guide junior engineers in India, establishing engineering standards, documentation practices, and operational excellence.
Qualifications
Your Knowledge & Skills
- 5+ years of hands-on experience in Snowflake data engineering, including ELT development at production scale.
- Strong expertise in SQL, Python, and Snowflake-specific features (Snowpipe, Streams/Tasks, Warehouses, RBAC).
- Experience with git-based code management and modern CI/CD tools (GitHub Actions, GitLab CI, Azure DevOps, etc.).
- Solid understanding of data modeling, performance tuning, and cost optimization in Snowflake.
- Proven ability to build and manage cloud-native data infrastructure (AWS/Azure/GCP exposure is a plus).
- Strong analytical and problemsolving abilities with the ability to handle complex data workflows and debugging.
- Excellent communication, leadership, and collaboration skills with a track record of guiding data engineering teams.
