Senior Data Engineer

Senior Data Engineer (Snowflake | Financial Data Platform)Pay Range on w2, US Citizens and GC Holders only, no exceptions.$77.00 - $93.95Contract duration: 7 monthsThe kind of person who thrives hereThis role is ideal for someone who has already built or contributed to:Financial data warehouses or cost transparency platformsEnterprise Snowflake implementationsLarge-scale data modeling environments tied to business finance or operationsLocationsWe are hiring across multiple major hubs:Burbank / Glendale, CA (Primary Hub)Orlando, FLSeattle, WAHybrid work model with collaboration on-site expected depending on location and team alignmentWe’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 excitingYou’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 pipelinesWork with financial, operational, and spend data at scaleInfluence how technology costs and investments are measured and optimizedPartner closely with finance, engineering, and product stakeholdersWork in a highly visible environment where your work directly impacts strategic decisionsThis is a rare opportunity to shape a platform that drives financial transparency and operational intelligence across a complex enterprise ecosystem.What you’ll doDesign, build, and maintain scalable data pipelines in SnowflakeDevelop robust data models, data marts, and semantic layersIngest and transform enterprise financial datasets (GL, budgets, vendor invoices, headcount, spend data)Build and optimize cost allocation and financial modeling logic using SQL and PythonPartner with finance and technology teams to translate business requirements into scalable data solutionsImplement orchestration and workflow automation using tools like dbt, Airflow, or Snowflake TasksEnsure strong data quality, auditability, and reconciliation frameworksSupport production systems with performance tuning, monitoring, and continuous improvementWhat we’re looking for5+ 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 processingExperience building enterprise-scale data pipelines and data modelsExposure to financial datasets such as GL, budgeting, forecasting, spend, or cost allocationExperience with orchestration tools (dbt, Airflow, or equivalent)Strong understanding of data governance, data quality, and production reliabilityExcellent communication skills and ability to work cross-functionallyNice to haveExperience with Technology Business Management (TBM) frameworksExposure to enterprise finance systems (SAP, ServiceNow, Clarity, Cognos, etc.)Familiarity with Snowflake Cortex AI or generative AI capabilitiesExperience building financial cost transparency or chargeback models