Senior Software Engineer, Data Platform

Responsibilities

• Design, build, and operate distributed services and compute infrastructure for the data platform, including containerized AWS ECS workloads, autoscaling, and resource sizing.
• Own scalable data pipelines and data-moving services from ingestion and orchestration through transformation and delivery.
• Improve event-sourced data movement between production systems, data infrastructure, and downstream systems.
• Participate in data-platform on-call and own production issues in distributed data systems.
• Implement secure handling of participant and employer data through PII classification and masking, role-based access controls, encryption, key management, lineage, and audit trails.
• Lead the technical direction of an AI-ready data platform supporting unstructured data, AI tooling, and production model and AI workloads.
• Build interfaces for data engineers, analysts, and AI systems and move curated warehouse data into production services and downstream tools.
• Mentor engineers and analysts and raise standards for testing, code review, and operational readiness.

Requirements

• 5+ years of experience building and operating production software systems, including significant experience with data-intensive systems such as pipelines, streaming platforms, or data infrastructure.
• Experience designing distributed systems and reasoning about concurrency, backpressure, idempotency, partial failure, and related tradeoffs.
• Hands-on experience running, scaling, sizing, and tuning containerized workloads on AWS in production.
• Ability to independently own and improve complex production systems using automated testing, code review, CI/CD, and infrastructure as code such as Terraform.
• Experience with workflow orchestration at scale, including Airflow or equivalent tools.
• Strong interest in using AI tools and workflow automation as a primary way of working.
• Preferred: experience with event-sourced or append-only log systems, change data capture, Kafka, or Kinesis.
• Preferred: experience with cloud data warehouses such as Snowflake, including access control, performance tuning, and cost management.
• Preferred: experience deploying and operating machine learning models in production, particularly serving infrastructure and monitoring.
• Preferred: experience with data lakehouse architectures and open table formats such as Apache Iceberg or Delta Lake.
• Preferred: experience building AI-oriented data infrastructure, including MCP-based data access, AI data governance, and evaluation of AI-generated query responses.
• Preferred: background in fintech, financial services, or another regulated or compliance-driven industry.

Benefits

• 401(k) plan with dollar-for-dollar employer matching up to 4% of compensation, immediate vesting, and no plan fees.
• Health, dental, and vision insurance.
• Competitive time off and parental leave.
• Financial wellness support through Addition Wealth.
• Enhanced mental health support through Lyra.
• Fertility healthcare and family-forming benefits through Carrot.
• Student-loan resources through Candidly.
• Monthly work-from-home stipend and quarterly lifestyle stipend.
• Virtual social events and team offsites.
• Employment is at-will; the posting does not state a specific remote or office work arrangement beyond the work-from-home stipend.