Data Engineer; Financial Market Data)

We're hiring a Data Engineer on behalf of our client, a VC-backed, growth-stage startup based in Houston, Texas, to join their team. Founded about a year ago, the client is building an AI-native analytics platform for institutional investors. The team is small (4 people) and brings backgrounds from NASA, big tech and finance (JPMorgan).

The product uses multiple specialized AI agents to analyze news, market data, alternative data and fundamentals across all asset classes in real time. A synthesizer agent then turns all of this into a single, prioritized insight feed for hedge fund traders and analysts, replacing hours of manual work across Bloomberg and other sources. Insights are explainable and traceable, which is essential for compliance.

The platform is invite-only, already used by real hedge funds and trading houses, and under active development.

You’ll own the data foundation that powers these agents: ingesting real-time and historical data from leading market data and news providers, with a strong focus on CME and ICE, and making it reliable, traceable and ready for ML models and applied AI workflows. Since the client is based in the US, we’re looking for someone comfortable working in US time zones.

Candidates located in the US or LATAM are ideal.

• Build and maintain real-time and batch data pipelines ingesting data from CME, ICE, NYSE, Bloomberg and Refinitiv
• Integrate real-time data streams, including CME's Real-Time Futures and Options Web Socket API
• Build or integrate a Web Socket manager that handles separate per-user Web Socket connections to CME
• Orchestrate data workflows with Airflow and manage data storage in Supabase and Neo4j
• Deliver clean, well-structured data to the platform's ML models and multi-agent AI workflows
• Ensure data quality, lineage and traceability so that every insight can be explained and audited
• Design and build an integration that exports selected emails from Microsoft Outlook into a local folder watched by the platform
• Assess technical feasibility of the Outlook integration approach and propose the best solution
• Collaborate with the client's team on data architecture and delivery

• Strong data engineering experience with Python and SQL
• Hands-on experience working with financial market data
• Proven experience integrating CME Market Data, ideally the Real-Time Futures and Options Web Socket API
• Proven experience integrating ICE Market Data
• Experience with NYSE APIs
• Experience with Bloomberg API for news and market data
• Experience with Refinitiv (Reuters) API for news
• Experience building real-time and streaming data pipelines, including managing Web Socket connections at scale
• Experience with Airflow

• Experience with Supabase, Neo4j or Railway
• Experience preparing data for ML models or AI/LLM-based workflows
• Experience with S&P Global APIs
• Experience with Kpler API
• Experience with Reuters news content delivery APIs
• Experience with Barchart for real-time data and charts
• Experience with Trading View for real-time futures data and charts
• Experience integrating with Microsoft Outlook (rules, email export or automation)
• Familiarity with React

• Build the data backbone of an AI-native platform used by real hedge funds and trading houses
• Work with some of the most important real-time market data sources in the industry
• Solve challenging real-time data problems, from exchange feeds to per-user streaming
• Work closely with a small, experienced team with backgrounds from NASA, big tech and JPMorgan
• Have a direct impact on a growth-stage, VC-backed product at an early and exciting stage

• Interview with a Honeycomb Software recruiter - a conversation to align on your experience and expectations
• Technical interview with Honeycomb Software's technical expert
• Interview with the client's team