Role: Senior Data Engineer, Data Platforms (Financial Risk Focus)
Location: Chicago, IL 60604 - Hybrid - onsite 3 days per week
Duration: 08 Months with possibility of extension
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.
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.
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
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Spectraforce Technologies
Mar 03, 2026