Seniot Data Engineer
Listed on 2026-05-31
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IT/Tech
Data Engineer, Data Warehousing, Data Analyst, Data Security
Senior Data Engineer (Snowflake | Financial Data Platform) Pay Range on w2, US Citizens and GC Holders only, no exceptions.
- $77.00 - $93.95
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
We are hiring across multiple major hubs:
- Burbank / Glendale, CA (Primary Hub)
- 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.
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
- 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
- Experience with Technology Business Management (TBM) frameworks
- Exposure to enterprise finance systems (SAP, Service Now, Clarity, Cognos, etc.)
- Familiarity with Snowflake Cortex AI or generative AI capabilities
- Experience building financial cost transparency or chargeback models
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