1018- Data Engineer

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 a real-time market data ingestion service consuming streaming equity data via WebSockets from Polygon.io (now Massive.com).
• Handle high-throughput data streams covering approximately 1,500 equities (~60–70% of the U.S. stock market).
• Aggregate and organize streaming data by time slices, preparing it for model consumption.
• Implement redundancy mechanisms, including failover to the 15-minute delayed stream if the real-time feed is interrupted.
• Deliver processed data to the trading model (a C-based script running on AWS EC2) on a daily cycle.
• Validate and maintain the existing historical data pipeline that pulls options and equity data from S3.
• Ensure historical data is updated daily and pipeline-ready for back-testing and model input.
• Work with data sourced from Polygon.io (equities) and CBOE (options) flat files.
• Instrument the pipeline with monitoring and alerting (e.g., Prometheus) to track message throughput, latest prices, and network health.
• Ensure the system meets the model’s requirement: if a full day’s data is not available, the model will not run, and all positions are exited as a safety measure.
• Proactively identify and resolve issues — do not wait to be asked.
• Integrate with an existing position monitoring component that syncs current holdings from the firm’s brokerage account.
• Coordinate with a DevOps engineer responsible for Kubernetes scheduling, deployments, and infrastructure.
• Participate in weekly syncs with the CTO and broader team; communicate blockers Immediately.

Requirements:

• 3+ Years of experience as a Data Engineer.
• Proven experience building and operating real-time streaming data pipelines in a production environment.
• Strong proficiency in Go (preferred for new development) and/or C (legacy system familiarity).
• 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.

It´s a Plus:

• 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.