Data Integration Lead

Summary:

Experienced Data Engineer with 10–12 years of hands-on expertise in designing and scaling enterprise-grade data solutions. Proven track record in building robust ETL pipelines, architecting cloud-native data platforms, and driving performance across large-scale systems. Adept at translating business needs into technical solutions, mentoring teams, and optimizing data workflows for analytics and operational excellence.

Key Responsibilities:

• ETL/ELT Development: Architect and maintain high-performance data pipelines using Ab Initio, handling complex transformations and large data volumes.

• Cloud Data Engineering: Build and optimize data platforms on AWS, leveraging services like S3, Lambda, Glue, and IAM for secure, scalable workflows.

• Snowflake Expertise: Design efficient schemas, implement clustering strategies, and tune performance for analytics workloads in Snowflake.

• Advanced SQL: Develop complex queries, stored procedures, and data validation logic to support reporting, analytics, and downstream systems.

• Data Modeling & Governance: Lead efforts in dimensional modeling, metadata management, and data lineage to ensure consistency and compliance.

• Performance & Quality: Conduct tuning across ETL jobs and cloud components; implement data quality frameworks to ensure reliability.

• Cross-Functional Collaboration: Partner with analysts, data scientists, and business stakeholders to deliver scalable, value-driven solutions.

• Mentorship & Leadership: Guide junior engineers, enforce best practices, and contribute to architectural decisions and roadmap planning.

• Innovation & Automation: Evaluate new tools, drive automation initiatives, and continuously improve pipeline efficiency and deployment velocity.

• Leverage industry best practices and methods.

• Define documentation to support the implementation of best practices.

• Good communication and stakeholders management.