Senior Data Engineer — Snowflake & Cloud Finance Analytics

Quantiphi; United States; Remote; USD 130,000 - 180,000; Full time

Job summary

Quantiphi is seeking a senior data engineer to build and modernize cloud data platforms for asset-based finance investment and portfolio analytics. The role blends hands-on pipeline development with financial data modeling, legacy migration, and coordination across engineering and quantitative teams.

The ideal candidate will design Snowflake data lake architectures, develop ETL/ELT workflows, and ensure data quality for finance analytics.

Qualifications

• 8+ years of experience in data engineering, building and optimizing data pipelines and workflows.
• Strong quantitative finance knowledge, including cash flow or predictive models, backtesting, and calibration.
• 5+ years of advanced SQL experience, including complex joins, window functions, aggregations, and conditional logic.
• 5+ years of professional Python development for complex data processing and automation, using Pandas or Polars.
• Experience leading project delivery across requirements, design, build, testing, and launch; clear communication and change management skills.

Responsibilities

• Design and maintain Snowflake data lake architectures and cloud-native pipelines for finance analytics.
• Build ETL/ELT workflows that ingest, transform, and curate structured and unstructured data.
• Support reporting and analytics through data validation, reconciliation, and financial integrity checks.
• Plan and execute legacy platform migrations, including data mapping and transformation design.
• Break delivery work into stories, coordinate timelines, and support testing, cutover, and launch readiness.

Skills

Python development

SQL

Data modeling

Cloud data pipelines

Financial data analytics

Tools

Snowflake

Pandas

Polars

Job description

Quantiphi is seeking a senior data engineer to build and modernize cloud data platforms for asset-based finance investment and portfolio analytics. The role blends hands-on pipeline development with financial data modeling, legacy migration, and coordination across engineering and quantitative teams.

The ideal candidate will design Snowflake data lake architectures, develop ETL/ELT workflows, and ensure data quality for finance analytics.