Information Technology - ETL Developer

The ETL Developer will lead the design, development, and implementation of an enterprise data ecosystem supporting business intelligence, advanced analytics, and regulatory reporting.

The role focuses on building and maintaining data warehousing solutions—particularly to support credit risk modeling—while contributing to data modernization and platform consolidation initiatives.

This position requires strong expertise in Snowflake, data architecture, ETL/ELT development, and large-scale data engineering.

• Provide strategic direction for data architecture, platforms, and governance, ensuring scalable and secure solutions aligned with business objectives.
• Lead the end-to-end design and implementation of a modern enterprise data ecosystem, including migration of legacy systems into a consolidated cloud environment.
• Architect, optimize, and maintain data warehouse structures in Snowflake to support complex credit risk models and regulatory requirements.
• Build and enhance high-performance ETL/ELT pipelines using Python, integrating data from multiple sources into centralized repositories.
• Develop and manage advanced data workflows using orchestration tools such as Airflow to ensure reliable, high-availability data feeds.
• Drive the unification of fragmented data sources into a cohesive data platform following best practices in data modeling.
• Lead technical workshops to gather business and technical requirements relevant to data warehousing and credit risk modeling.
• Perform coding, testing, deployment, and validation of ETL/ELT processes to ensure data accuracy and consistency.
• Conduct technical evaluations of emerging data technologies, creating proof-of-concepts to validate architectural strategies.
• Serve as a key technical liaison between engineering teams and other stakeholders.

• 8+ years of experience in data engineering or data warehousing, including leadership in large-scale modernization or consolidation projects.
• Deep expertise in Snowflake architecture, including optimization, tuning, data sharing, and cost governance.
• Strong proficiency in SQL and dimensional data modeling.
• Mastery of Python for data transformation, automation, and API integrations.
• Extensive experience with enterprise orchestration tools such as Apache Airflow.
• Bachelor's degree in Computer Science, Information Technology, or related field, or equivalent professional experience.
• Strong understanding of data architecture principles and modeling techniques, including those required for regulatory reporting.
• Excellent communication and presentation skills, with the ability to explain complex technical concepts to technical and executive audiences.
• Expertise in ETL/ELT patterns and data warehousing within financial risk or similar environments.

• Experience with Datastage ETL.
• Familiarity with CI/CD pipeline deployment processes.
• Background in financial services, risk, or regulatory reporting (preferred but not mandatory).