1018- Data Engineer

Location: Remote

Department: Information Technology

We need an English-fluent Data Engineer, based in Latin America, available to work remotely.

We are looking for someone with exceptional communication and relationship-building skills, who embraces changes while maintaining strong attention to detail. An interested and proactive person, who's constantly learning and improving their skills.

Are you the one we are looking for?

Responsibilities:

• Build and maintain a real-time market data ingestion service that consumes streaming equity data via WebSockets.
• Manage high-volume data streams.
• Aggregate and structure streaming data into time-based slices for model consumption.
• Implement reliability measures, including fallback if the real-time feed is interrupted.
• Deliver processed data daily to a trading model.
• Maintain and validate the historical data pipeline pulling equity and options data from S3.
• Ensure historical datasets are updated daily and ready for back-testing and model input.
• Work with data sources including Polygon.io (equities) and CBOE options flat files.
• Add monitoring and alerting to track system health, throughput, and pricing updates.
• Ensure data completeness — the model requires a full trading day of data to run successfully.
• Proactively identify and resolve issues to keep the system running smoothly.
• Integrate with an existing position monitoring component that syncs brokerage account holdings.
• Collaborate with a DevOps engineer on Kubernetes deployments and infrastructure.
• Participate in weekly syncs with the CTO and team, communicating progress and blockers clearly.

Requirements:

• 5+ Years of experience as a Data Engineer.
• Proven experience building and operating real-time streaming data pipelines in a production environment.
• Proven experience in Go (Experience in new development is strongly preferred).
• Proven experience in C (legacy system).
• Hands-on experience consuming market data or high-throughput event streams via WebSockets.
• Familiarity with AWS services (EC2, S3) and containerized environments (Kubernetes).
• Experience with monitoring/observability tooling such as Prometheus, Grafana, or similar.
• Demonstrated ability to work independently, take initiative, and communicate proactively when facing blockers.
• Comfort working in a small, fast-moving team with minimal oversight.
• Prior experience in quantitative finance, hedge funds, or fintech data infrastructure.
• Experience with Polygon.io / Massive.com APIs and data formats.
• Background in financial market data (equities, options) and familiarity with concepts like tradable universes and position management.
• Experience with message queuing, stream processing frameworks, or time-series data aggregation.