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Data Engineer Job in USA 2026 with H-1B Visa Sponsorship | SANS

Data Engineer Job in USA 2026 with H-1B Visa Sponsorship | SANS

Data Engineer Job in USA 2026 with H-1B Visa Sponsorship | SANS

A leading quantitative research organization within the financial services sector in New York City, USA, is hiring a Data Engineer for 2026 with H-1B visa sponsorship available for qualified international professionals. This is a high-impact, front-office data engineering role embedded in the research function of a hedge fund, focused on building and scaling advanced data ingestion pipelines for alternative data into Snowflake.

This opportunity is designed for experienced data engineers who thrive in fast-paced financial environments and are comfortable owning mission-critical data pipelines end to end. You will work with large, complex, non-traditional datasets such as web-scraped data, consumer behavior data, geolocation data, sentiment data, and other unconventional data sources used to generate investment insights.

The environment is performance-driven, technically demanding, and highly collaborative, offering long-term career growth in one of the most advanced data ecosystems in finance.

About the Role

The core mission of this role is to design, build, and operate scalable data ingestion and transformation systems that bring raw external data into Snowflake and integrate it into the firm’s internal analytics platforms. You will work primarily in Python and SQL, using modern data tooling such as Prefect and DBT, while collaborating closely with researchers, data scientists, and other engineers.

This is not a maintenance role. You will be expected to improve data quality, reliability, observability, and workflow efficiency while operating in a high-ownership culture where engineers are responsible for the systems they build.

About the Hiring Firm

The hiring organization is a research-driven hedge fund operating in Manhattan that uses sophisticated data science and alternative data to drive investment decisions. The firm invests heavily in data infrastructure and engineering excellence and supports international professionals through structured onboarding and H-1B visa sponsorship.

The culture emphasizes speed, accountability, technical depth, and close collaboration between engineering, research, and business teams.

Responsibilities

  • Design and build ETL pipelines to ingest data from APIs, S3, SFTP servers, and vendor data shares into Snowflake
  • Develop and maintain Python-based data ingestion and processing systems
  • Integrate raw datasets into internal analytics platforms using SQL and Python frameworks
  • Orchestrate workflows using Prefect and manage transformations using DBT
  • Improve data quality, monitoring, alerting, and pipeline reliability
  • Optimize performance and scalability of data ingestion and transformation processes
  • Collaborate with data scientists and researchers to understand downstream data usage
  • Own production pipelines, including operational support and issue resolution

Requirements

  • Strong experience as a Data Engineer in financial services, hedge funds, or capital markets
  • Hands-on expertise with Snowflake, Python, SQL, ETL pipelines, APIs, S3, and SFTP
  • Proven experience working with alternative or large-scale non-traditional datasets
  • Experience with DBT and workflow orchestration tools such as Prefect
  • Strong Python skills using libraries such as Pandas, NumPy, SciPy, or similar
  • Ability to work in high-pressure, fast-delivery environments with a strong ownership mindset
  • Excellent communication skills and ability to work cross-functionally
  • Eligible for H-1B visa sponsorship (no OPT/CPT)

Click Here to Apply

Conclusion

This is a rare opportunity to secure a high-impact Data Engineer role in the USA in 2026, with H-1B visa sponsorship, at the heart of a data-driven hedge fund. For international candidates seeking elite exposure, complex data challenges, and long-term growth in U.S. financial technology, this role offers exceptional career leverage and technical depth.

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