Big Data Developer

Full-Time | Onsite 5 Days/Week | Midtown East, Manhattan | NYC

A leading global market maker is seeking a highly analytical Big Data Engineer to join the firm’s Transaction Reporting & Data Analytics group. This role sits at the center of the firm’s global trading ecosystem, responsible for processing massive datasets, building scalable data pipelines, and extracting critical insights that power regulatory reporting, trading analytics, and firmwide decision-making. You will work directly with quants, traders, and technology teams to ensure accurate, real‑time data across global markets.

• Process, transform, and analyze large-scale datasets across global trading and transaction reporting systems.
• Build, maintain, and optimize data pipelines, ETL frameworks, and high-performance data ingestion workflows.
• Conduct hands‑on SQL and Python development to extract insights, validate transaction flows, and support regulatory reporting functions.
• Partner with global stakeholders—including trading, risk, compliance, and engineering—to understand data needs and deliver actionable analytics.
• Perform root‑cause analysis on data quality issues, ensuring accuracy, consistency, and completeness across all market and transactional data.
• Support large real‑time and historical data environments, potentially including kdb+/q or other time‑series databases.
• Develop dashboards, analytics tools, and automated reporting solutions to deliver timely insights to senior leadership.

• 3–7+ years of experience in big data analytics, data engineering, or transaction data processing, ideally within a market maker, hedge fund, or trading firm.
• Strong hands‑on expertise with Python and SQL (Postgres, Oracle, or similar).
• Experience working with large-scale, high-throughput datasets and distributed data environments.
• Familiarity with KDB+/q, time‑series data, or low-latency data stacks is highly preferred.
• Background in global transaction reporting, reg‑tech, market data, or trade lifecycle systems is a major advantage.
• Strong analytical mindset with the ability to diagnose data issues, interpret complex data structures, and translate findings for technical and non‑technical teams.
• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related technical field.