Lead Data Engineer

Key Responsibilities:

• Designing and implementing scalable data pipelines
• Building and managing data warehouses and data lakes
• Ensuring data quality and implementing data management best practices
• Optimizing data storage and retrieval processes
• Collaborate closely with data scientists, analysts, and product teams to support analytics and machine learning initiatives.
• CI/CD orchestration and automation tools: Experience with tools such as Jenkins, GitHub etc.
• Monitor and tune Snowflake query performance, warehouse usage, and credit consumption.
• Collaborate closely with data scientists, analysts, and product teams to support analytics and machine learning initiatives.
• Design and enforce row-level access policies and dynamic masking in Snowflake for sensitive data fields (PII, financials).
• Enabled data sharing with external teams using secure shares and reader accounts while maintaining strict RBAC controls.
• Experience with ETL /Scheduler tools.
• Strong interpersonal, written, and verbal communication skills to interact effectively across teams and stakeholders.
• Designing semantic layers, aggregate tables, and data models (Star/Snowflake) to support scalable, governed, and business-friendly analytics architecture.

Good to have:

• Machine Learning and AI/LLM model training / implementation.
• Background in data observability, lineage tracking, or metadata management tools