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Rogo

Software Engineer: Financial Data

New York City$250k–$315kfulltimemidAdded today

About this role

Join Rogo's Financial Data team as a Backend Engineer to build and scale critical data infrastructure powering AI-driven financial analysis. You'll design robust pipelines ingesting and transforming vast financial datasets from multiple sources, ensuring the data quality that investment professionals demand.

What you'll do

  • Design and build scalable data processing pipelines handling millions of documents daily with low latency
  • Architect systems integrating heterogeneous financial data sources into reliable, queryable platforms
  • Own end-to-end data infrastructure from conception through production deployment
  • Collaborate with Core AI team to optimize data structure and quality for model performance
  • Build secure, compliant data integrations meeting enterprise privacy and reliability standards
  • Lead by example through code quality and decision-making that elevates the team

What they're looking for

  • Python backend and API development
  • Strongly-typed languages (Java preferred, Rust, or C++)
  • Google Cloud Platform (GCP) or equivalent cloud infrastructure
  • Distributed systems design (async patterns, streaming, queuing, caching)
  • SQL and relational database optimization
  • NoSQL, Redis, and columnar data stores (BigQuery, Snowflake, Redshift)
  • Large-scale data pipeline architecture (streaming and batch)
  • Observability systems (logging, metrics, tracing)
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Rogo

Rogo builds a financial AI platform with a focus on data-driven insights and user experience. The company is hiring Analytics Engineers to develop data pipelines and reporting tools, and Design Engineers to enhance its design system and user interactions.

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Likely interview questions

  • Walk us through a complex data pipeline you've built at scale—what were the key architectural decisions and how did you handle failures?
  • Describe your experience integrating data from multiple heterogeneous sources. What challenges did you face and how did you ensure reliability?
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