Data EngineerJob description:We are looking for a strong Data Engineer to help modernize our core data and API platforms in our New York office. Working closely within our collaborative data team, you will bridge traditional quantitative financial systems and modern cloud infrastructure building robust pipelines, for handling complex market data analytics, supporting both high-performance trading platforms and emerging AI data workflows.
Responsibilities:- Modernize legacy workflows into modern ELT/orchestration; design, build, and maintain production-grade pipelines (SQL, Python, Snowflake, dbt) moving data from on-prem systems (e.g., SQL Server), vendor feeds, APIs, and flat files into the cloud.
- Ingest, structure, and optimize complex financial datasets specializing in high-precision pricing analytics, yield curves, volatility surfaces, risk metrics, and P&L attribution.
- Diagnose slow queries and bottlenecks; implement indexing, clustering, caching, and pre-aggregation for Power BI and internal tools. Expand Python-based API infrastructure to scale dataset access across the firm.
- Build robust data pipelines for unstructured document storage, parsing, and ingestion. Develop and maintain semantic layers and structured feature sets tailored for AI applications
- Implement automated checks for missing/stale data, schema drift, duplicates, and outliers. Build dashboards for market data anomalies and maintain a user-facing data catalog (datasets, lineage, ownership, and quality rules).
- Balance modernization initiatives with day-to-day troubleshooting, user support, and vendor follow-ups.
Required qualities and skills:- 5-7 years in data engineering, analytics engineering, or quantitative data roles, ideally within a hedge fund, asset manager, or systematic trading shop.
- Advanced SQL (performance tuning, complex transforms, dimensional modeling) and hands-on Python (Pandas, Polars, and API integrations).
- Experience with Microsoft SQL Server, a modern cloud data warehouse (Snowflake preferred), and transformation tools like dbt. Familiarity with AI toolset in cloud platform.
- Strong, hands-on knowledge of quantitative financial concepts specifically deep familiarity with Fixed Income, yield curves, fx, volatility datasets, trade lifecycles, and reference data feeds (e.g., Bloomberg, LSEG).
- Clear communicator comfortable partnering with technical and business stakeholders alike. A can-do attitude for tasks both big and small.
Desirable skills:- Experience with high-frequency tick databases or specialized analytical engines (e.g., Azure Data Explorer/KQL).
- Exposure to streaming or event-driven patterns (Event Hubs or Change Data Capture/CDC).
- BI tool optimization experience (Power BI or Tableau) and workflow orchestrators.
- Experience building semantic layer
Work status and location:Pay range in New York:
- Exact compensation may vary based on skills, experience, and location.
- Base salary - $150,000-180,000/year
