Role Overview:
We are seeking a Senior/Lead Data Engineer to drive the modernization of our enterprise data warehouse into a cloud-native analytics platform. This is a hands-on leadership role where you will design and build reliable ingestion pipelines, dimensional models, and robust operational controls. You will work closely with architects and platform teams to transition from legacy systems to a high-performance AWS + Snowflake ecosystem.
Key Responsibilities:
1. Architecture & Pipeline Engineering
- Snowflake Design: Architect and build data warehouse layers, including RAW, ODS, and DW schemas, tables, and views.
- Ingestion & Orchestration: Implement end-to-end pipelines using Snowflake-native features such as Snowpipe, Tasks, Streams, and Stored Procedures.
- Cloud Integration: Manage data flow from AWS S3 through storage integrations and stages into the warehouse.
2. Data Modeling & Optimization
- Dimensional Modeling: Develop and maintain complex Fact and Dimension models to support business intelligence.
- Performance Tuning: Optimize transformations and aggregates to ensure high-speed query performance and cost-efficiency.
- Data Quality: Implement automated reconciliation, validation, and DQ checks to ensure cross-environment consistency.
3. Operational Excellence & Leadership
- Production Readiness: Build error-handling patterns, rerun/recovery logic, and comprehensive runbooks for monitoring support.
- Technical Guidance: Lead the technical direction for the engineering team, providing mentorship and conducting code reviews.
- Cross-Functional Collaboration: Support SIT/UAT activities and collaborate with DevOps for seamless CI/CD deployments.
Qualifications
Must-Have Expertise:
- Experience: 5+ years in Data Engineering or Enterprise Data Warehousing.
- Technical Mastery: Expert-level SQL (window functions, complex joins) and hands-on experience with Snowflake (or a proven ability to transition from another Cloud DW).
- Modeling: Strong grasp of dimensional modeling (Star/Snowflake schema).
- Production Standards: Experience with cloud integration patterns (S3) and operational support (logging, retries).
Preferred (Plus Points):
- Experience migrating legacy Oracle DW to the cloud.
- Proficiency in handling semi-structured data (JSON/VARIANT).
- Knowledge of CI/CD for Data (Git-based workflows) and BI tools like Tableau.
- Certifications in AI, ML, or GenAI.
