Senior Software Engineer, Data Platform

Human Interest is a fintech company working to expand access to retirement benefits for employees at small and medium-sized businesses. The Senior Software Engineer on the Data Platform team will build and operate distributed systems, data pipelines, and compute infrastructure, while leading the platform’s evolution toward AI-ready architecture and mentoring engineers and analysts.

Responsibilities:

• Design, build, and operate the distributed services and compute infrastructure behind our data platform, including containerized workloads on AWS ECS, autoscaling and resource sizing, and the orchestration layer that coordinates them
• Own end-to-end design and development of scalable data pipelines and data-moving services, from ingestion and orchestration through transformation and delivery
• Improve how event-sourced data moves from our production systems into our data infrastructure and back out to other systems
• Participate in on-call for the data platform, and own production issues in distributed data systems end to end
• Ensure participant and employer data is handled securely as it moves through the platform, including PII classification and masking, role-based access controls and least-privilege patterns, encryption and key management, lineage, and the audit trails our SOC 2 and regulatory obligations depend on
• Lead the technical direction and evolution of our data platform as we move toward an AI-first data infrastructure. You will design for AI consumption, unstructured data access, and integration with AI tooling from the ground up, including the pipelines and infrastructure that support model and AI workloads running in production
• Build the interfaces that data engineers, analysts, and AI systems use, and the systems that move curated data back out of the warehouse into production services and downstream tools
• Mentor engineers and analysts and raise the technical bar across the team, setting the standard for testing, code review, and operational readiness on the data stack

Requirements:

• 5+ years of experience building and operating production software systems, with significant time spent on data-intensive systems such as data pipelines, data streaming platforms, and data infrastructure
• Demonstrated experience designing distributed systems and services, with the ability to reason clearly about software concepts like concurrency, backpressure, idempotency, partial failure, and the tradeoffs between them
• Hands-on experience running containerized workloads in production on AWS including scaling, resource sizing, and performance and cost tuning under real load
• The ability to independently own and improve complex production systems, alongside the software engineering practices that go with them: automated testing, code review, CI/CD, and infrastructure as code such as Terraform
• Experience with workflow orchestration at scale, including Airflow or equivalent tools
• A strong desire to leverage AI tools and workflow automation as the primary way work gets done, not just to augment work
• Hands-on experience with event-sourced or append-only log systems, or with change data capture and streaming platforms (e.g. Kafka or Kinesis)
• Working knowledge of cloud data warehouse technologies, including Snowflake or equivalent, covering access control, performance tuning, and cost management
• Experience getting machine learning models into production and keeping them healthy there. We are interested in the engineering side of ML in production rather than model development itself (e.g. serving infrastructure and monitoring)
• Experience with data lakehouse architectures and open table formats such as Apache Iceberg or Delta Lake
• Experience building data infrastructure to support AI-driven data access, such as exposing data assets via MCP, implementing governance frameworks for AI data access, and curating, monitoring, and evaluating the quality of AI-generated query responses
• Background in fintech, financial services, or another highly regulated or compliance-driven industry