Data engineer /ETL Developer (Strong SQL + Snowflake+Python) –
Local to Chicago (primary and strongly preferred).
• Reports to the Wabash location.
• Hybrid schedule: 3 days/week on site (current anchor days: Tuesday, Wednesday, Thursday).
• Standard working hours: 8:00 AM – 5:00 PM CT.
8+ years in data engineering / warehousing
• Strong SQL + Snowflake
• Solid Python (for framework work + data transformation)
• Experience with large-scale migrations or platform modernization
• Background in FS, risk, or regulatory reporting (nice-to-have, not mandatory)
Project & Technical Scope
• Role supports a new enterprise data platform build-out to replace/sunset legacy IBM DataStage + Netezza/RAQ systems.
• Tech stack includes: Snowflake, SQL, Python (strongly desired), Airflow (orchestration), and custom internal Python-based frameworks.
• Focus areas:
o Data engineering + ETL development
o Participation in design/architecture (majority still hands-on development)
o Data modeling (nice to have)
Domain Focus
• Supports financial risk and regulatory reporting domains including:
o Credit Risk, Market Risk, Model Risk
o CCAR, FR Y 14, SECL, and other regulatory submissions
• Financial industry experience is highly preferred (helps candidates acclimate much faster).
Job Description*
Project Overview: Lead the design, and implementation of the enterprise data ecosystem, driving the modernization and consolidation of data platforms to support business intelligence, advanced
analytics, and regulatory reporting. This includes a critical focusing on the design, development, and maintenance of data warehousing solutions that support credit risk modeling.
Contractor's Role:
· Provide strategic vision for data architecture, platforms, and governance, translating business objectives into effective, scalable, and secure technical solutions.
· Lead the end-to-end design and implementation of a scalable enterprise data ecosystem, migrating legacy systems into a modern, consolidated cloud environment.
· Architect and maintain robust data warehouse structures in Snowflake to support complex credit risk models, ensuring data lineage, accuracy, and auditability for regulatory compliance.
· Build and optimize high-performance ETL/ELT pipelines using Python, ensuring seamless data flow from disparate sources into the central warehouse.
· Design and manage complex workflows using data orchestration tools (e.g., Airflow) to ensure high availability and reliability of data feeds.
· Drive the transition from fragmented data silos to a unified platform, implementing best practices in data modeling.
Experience Level - 3 - Senior
· 8+ years in Data Engineering, with a proven track record of leading large-scale data modernization or consolidation projects.
· Deep experience in Snowflake architecture, including performance tuning, data sharing, and cost management.
· Expert-level knowledge of SQL and dimensional data modeling techniques.
· Mastery of Python for data manipulation, automation, and API integrations.
· Extensive experience with enterprise-grade orchestration tools (e.g., Apache Airflow)
Qualifications
· Bachelor's degree in Computer Science, Information Technology, or a related field, or equivalent professional experience.
· In-depth knowledge of data architecture principles, data modeling techniques (including dimensional modeling for regulatory reporting).
· Strong communication and presentation skills, with the ability to convey complex technical concepts and strategy, including regulatory requirements related to data, to both technical and executive-level stakeholders.
· Expertise in data warehousing and ETL/ELT patterns, particularly within a financial risk context.
Nice to Have
· Datastage ETL experience.
· CI/CD pipeline deployment processes.
Daily Tasks and Responsibilities
· Lead technical workshops to capture business and technical requirements, particularly those related to data warehousing solutions that support credit risk modeling.
· This includes coding, testing, and deploying processes to extract, transform, and load data from various sources.
· validating data to ensure accuracy and consistency, which is crucial for reliable analysis.
· Perform technical evaluations of new data technologies and features, building proof-of-concepts to validate architectural approaches.
· Serve as the key technical liaison between the engineering teams.
Thanks & Regards,
Kiran Kumar
Email:
Ki...@sapphiresoftwaresolutions.com
Sapphire Software Solutions Inc | Certified Minority Business Enterprise (MBE)