Senior Software Engineer, Data Platform

Human Interest

2d • $190,000 - $230,000

About The Position

Human Interest is on a mission to ensure that people in all lines of work have access to retirement benefits. More than half of all working Americans are not saving enough for their future. Too often, it’s because they are employed by a company that doesn’t offer a retirement plan. Human Interest is changing that by making it affordable and accessible for small and medium-sized businesses to offer employees a path to financial independence through retirement savings. We’re a high-growth fintech company changing the retirement industry. We are backed by a number of investors. This includes funding from Marshall Wace and Baillie Gifford, as well as top investors such as BlackRock, TPG (The Rise Fund), SoftBank, Glynn Capital, NewView Capital, USVP, Wing, Uncork, and more.

About the role
As a Senior Software Engineer on the Data Platform team, you will build and operate the distributed systems and services that Human Interest's data platform runs on, at a pivotal moment in Human Interest's growth. This role exists to own the infrastructure and compute layer that moves data reliably at scale. You will drive the evolution of our data platform toward an architecture that scales for AI consumption and for Human Interest's next growth stage.

This is a software engineering role in the data domain. You will spend your time designing services, reasoning about failure modes, and tuning distributed compute rather than authoring analytics models. We are looking for engineers who have built production systems and moved into the data world, and who want to keep building systems there. This is a high-ownership role where your architectural decisions will have a direct and visible impact on Human Interest's capabilities.

About the team
The Data Platform team at Human Interest owns the data stack from ingestion and orchestration through transformation, governance, and delivery to BI tools. Our stack currently includes Snowflake, dbt, Airflow, Meltano, and AWS. We're a small, highly collaborative team embedded within the HI Tech organization, working closely with Analysts, Finance, Product, and engineering teams to ensure that the data people rely on is trustworthy and accessible.

You'll shape how we evolve our architecture towards AI-consumption and to set the standard for how production data systems are built, deployed, and operated at Human Interest. The team actively uses AI tools as part of our development workflow, and we expect this role to help drive and expand that practice across the team.

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.

Nice To Haves

• 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.

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.

Benefits

• A great 401(k) plan: Our own! Our 401(k) includes a dollar-for-dollar employer match up to 4% of compensation (immediately vested) and $0 plan fees
• Top-of-the-line health plans, as well as dental and vision insurance
• Competitive time off and parental leave
• Addition Wealth: Unlimited access to digital tools, financial professionals, and a knowledge center to help you understand your equity and support your financial wellness
• Lyra: Enhanced Mental Health Support for Employees and dependents
• Carrot: Fertility healthcare and family forming benefits
• Candidly: Student loan resource to help you and your family plan, borrow, and repay student debt
• Monthly work-from-home stipend; quarterly lifestyle stipend
• Engaging team-building experiences, ranging from virtual social events to team offsites, promoting collaboration and camaraderie.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed