Senior Data Engineer

Verition Fund Management LLC (“Verition”) is a multi-strategy, multi-manager hedge fund founded in 2008. Verition focuses on global investment strategies including Global Credit, Global Convertible, Volatility & Capital Structure Arbitrage, Event-Driven Investing, Equity Long/Short & Capital Markets Trading, and Global Quantitative Trading.

We are seeking a Senior Data Engineer to help design, build, scale, and support Verition’s Data Platform in the cloud. This role sits at the intersection of data engineering, cloud infrastructure, and stakeholder partnership, with a focus on delivering high-quality, reliable datasets that power investment, risk, and operational workflows across the firm.

The Data Engineering team owns several core data products, including market data, internal data, and web scraping. This role will partner closely with Portfolio Managers, Quants, Data Scientists, and Risk, Operations, and Technology teams to onboard new data sources, improve data quality, and expand platform capabilities. The role reports to the Data Engineering Manager.

Responsibilities

• Partner with investment, risk, & operational teams to drive adoption of centralized data.
• Design, build, & maintain data platform infrastructure in the cloud.
• Design & maintain high-volume ingestion pipelines from APIs, S3, & SFTP into Snowflake.
• Design & maintain scalable transformation pipelines in Snowflake using dbt.
• Curate & model internal portfolio, market, & web data for firm-wide use.
• Build reusable, well-governed data models that simplify consumption & lower compute costs.
• Apply strong SQL expertise to tune query performance & improve end-user experience.
• Maintain data quality SLAs through automated testing, validation, & anomaly detection.
• Support day-to-day operations, including data quality issues, vendor SLAs, & infra incidents.
• Contribute to system design, backlog refinement, & roadmap planning.
• Incorporate engineering best practices, including CI/CD, testing, docs, linting, & maintainability.

Required Qualifications

• 7+ years of experience in data engineering or software engineering3+ years of experience at a buy-side, capital markets, or closely related financial firm.5+ years optimizing queries in Snowflake, Databricks, BigQuery, or a similar cloud platform.5+ years designing, building, & operating data pipelines in Airflow or a similar orchestrator.5+ years designing complex data transformations & models using dbt, SQLMesh, or similar.3+ years maintaining AWS infrastructure using Terraform or similar infra-as-code tools.
• Strong communication skills & the ability to work directly with PMs, quants, analysts.

Preferred Qualifications

• Exposure to market data, e.g., Bloomberg, Fact
• Set, Refinitiv, exchange feeds, tick data.
• Exposure to portfolio & risk datasetsg., Position, P&L, Security master, Trade feeds, Pricing.
• Hand-on experience with data modeling techniques, e.g., dimensional, SCD2, time-series.

Experience independently debugging complex AWS infrastructure issues is a strong plus.