Software Engineer: Financial Data

Responsibilities

• Own the design and production operation of scalable systems that ingest, transform, and serve financial datasets.
• Build high-throughput, low-latency streaming and batch data pipelines handling millions of documents and datapoints daily.
• Integrate market data vendors, proprietary sources, and third-party financial datasets into reliable, queryable platforms.
• Partner with the Core AI team to structure, clean, and serve financial data for AI models and retrieval systems.
• Build secure, compliant integrations that protect enterprise customer data from ingestion through serving.
• Make architecture and implementation decisions that improve system scale, performance, reliability, and cost efficiency.
• Lead by example and contribute to a culture of technical excellence, learning, ownership, and collaboration.

Requirements

• Bachelor’s degree in Computer Science or a related field.
• 5+ years of professional software engineering experience building complex, data-intensive backend systems.
• 5+ years of hands-on experience with GCP or an equivalent cloud stack in production environments.
• Deep Python expertise for backend and API systems, plus proficiency in Rust, C++, or Java; Java experience is a strong plus.
• Strong experience designing large-scale distributed systems with asynchronous patterns, streaming, queuing, caching, and observability.
• Expertise with relational databases and SQL, including schema design, query optimization, and indexing, along with NoSQL, Redis, BigQuery, Snowflake, and Redshift.
• Experience building and operating reliable, high-throughput streaming and batch data pipelines integrating heterogeneous financial data sources.
• 3+ years of experience managing or working closely with globally distributed engineering teams.
• Exceptional communication skills and the ability to influence technical direction across teams without direct authority.
• Experience shipping high-quality products autonomously in unstructured, fast-moving environments.
• Demonstrated knowledge of corporate finance, capital markets, and financial data quality standards.

Benefits

• Opportunity to work on enterprise AI products used by leading financial institutions.
• Substantial ownership of technically demanding systems at a rapidly scaling company.
• Work alongside a high-performing team spanning AI and finance.
• Opportunity to work on financial-data and AI infrastructure at significant scale.