Sr. Data Engineer

Data Pipeline Development: Design, build, and maintain robust ELT (Extract, Load, Transform) pipelines using Snowflake to support data ingestion, integration, and transformation.

Technical Leadership: Lead offshore development teams in implementing best practices for data engineering and ELT development.

Data Integration: Collaborate with stakeholders to understand data sources and integration requirements, ensuring seamless connectivity and data flow between systems.

Performance Optimization: Optimize data pipelines for performance, scalability, and reliability, including query tuning and resource management within Snowflake.

Data Quality Assurance: Implement and monitor data validation procedures to ensure data accuracy and consistency across systems.

Collaboration and Communication: Work closely with project managers, data architects, and business analysts to align project milestones and deliverables with business goals.

Documentation: Create and maintain detailed documentation of data pipelines, data flow diagrams, and transformation logic.

Issue Resolution: Troubleshoot and resolve issues related to data pipelines, including job failures and performance bottlenecks.

Compliance and Security: Ensure all data management processes comply with data governance policies and regulatory requirements in financial services.

Bachelor’s degree in Computer Science, Information Technology, or a related field.

5+ years of experience in data engineering with a strong focus on ELT processes and data pipeline development.

Hands-on experience with Snowflake cloud data platform, including data sharing, secure views, and performance optimization.

Proficiency in SQL and familiarity with data integration and ETL/ELT tools.

AWS Technologies (Glue, EMR)

Python for data engineering workflows

Strong understanding of data engineering design patterns