Seniot Data Engineer

Senior Data Engineer (Snowflake | Financial Data Platform) Pay Range on w2, US Citizens and GC Holders only, no exceptions. • $77.00 - $93.95 Contract duration: 7 months The kind of person who thrives here This role is ideal for someone who has already built or contributed to: • Financial data warehouses or cost transparency platforms • Enterprise Snowflake implementations • Large-scale data modeling environments tied to business finance or operations Locations We are hiring across multiple major hubs: • Burbank / Glendale, CA (Primary Hub) • Orlando, FL • Seattle, WA Hybrid work model with collaboration on-site expected depending on location and team alignment We’re looking for a Senior Data Engineer to help build a next-generation enterprise financial data platform powered by Snowflake. This is a high-impact role where you’ll design and engineer the data foundation that enables financial transparency, cost analytics, and strategic decision-making across a large-scale global organization. If you enjoy building real data products—not just pipelines—and want to work on complex financial datasets at enterprise scale, this is a strong fit. Why this role is exciting You’ll be joining a team building a modern Technology Business Management (TBM) and financial data platform from the ground up in Snowflake. This environment is ideal for engineers who want to: • Build enterprise-grade data platforms, not just pipelines • Work with financial, operational, and spend data at scale • Influence how technology costs and investments are measured and optimized • Partner closely with finance, engineering, and product stakeholders • Work in a highly visible environment where your work directly impacts strategic decisions This is a rare opportunity to shape a platform that drives financial transparency and operational intelligence across a complex enterprise ecosystem. What you’ll do • Design, build, and maintain scalable data pipelines in Snowflake • Develop robust data models, data marts, and semantic layers • Ingest and transform enterprise financial datasets (GL, budgets, vendor invoices, headcount, spend data) • Build and optimize cost allocation and financial modeling logic using SQL and Python • Partner with finance and technology teams to translate business requirements into scalable data solutions • Implement orchestration and workflow automation using tools like dbt, Airflow, or Snowflake Tasks • Ensure strong data quality, auditability, and reconciliation frameworks • Support production systems with performance tuning, monitoring, and continuous improvement What we’re looking for • 5+ years of experience in Data Engineering (seniority and depth matter more than title) • Strong hands-on experience with Snowflake (pipelines, modeling, data warehousing) • Advanced SQL expertise (window functions, CTEs, performance tuning) • Proficiency in Python for ETL/ELT, automation, or data processing • Experience building enterprise-scale data pipelines and data models • Exposure to financial datasets such as GL, budgeting, forecasting, spend, or cost allocation • Experience with orchestration tools (dbt, Airflow, or equivalent) • Strong understanding of data governance, data quality, and production reliability • Excellent communication skills and ability to work cross-functionally Nice to have • Experience with Technology Business Management (TBM) frameworks • Exposure to enterprise finance systems (SAP, ServiceNow, Clarity, Cognos, etc.) • Familiarity with Snowflake Cortex AI or generative AI capabilities • Experience building financial cost transparency or chargeback models