Sr. Data Engineer (contract)

Senior Data Engineer, Data Platforms (Financial Risk Focus) 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. Pay Rate Range 67 - 74 USD hourly Additional Notes The above listed pay range is a good faith estimate of what the employer reasonably expects to pay for this position. Benefits Information Optional benefits offering includes medical, dental, vision and retirement benefits via Hiregenics.