Senior Software Engineer, Data Platform

Human Interest

. Design, build, and operate distributed services and compute infrastructure for the data platform, including containerized workloads on AWS ECS, autoscaling, resource sizing, and orchestration .

Posted 10/6/2026full-timeRemote • United StatesSenior💰 $190,000 - $230,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and operating distributed data systems, with a strong focus on building scalable data pipelines and leveraging AI tools for workflow automation. Proficient in securing data through PII classification and compliance with SOC 2 standards.

Highest-signal resume keywords

AWS Containerized WorkloadsData Pipeline DevelopmentWorkflow Orchestration (Airflow)Infrastructure as Code (Terraform)Data Security and Compliance

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data Streaming PlatformsDistributed Systems DesignAutomated TestingCI/CD PracticesEvent-Sourced SystemsMachine Learning Model DeploymentData Lakehouse ArchitecturesChange Data CapturePerformance TuningCost Management

Soft Skills

MentoringTechnical LeadershipProblem Solving

Tools & Technologies

AWS ECSApache IcebergDelta LakeKafkaKinesisSnowflake

Industry Keywords

FintechFinancial ServicesRegulatory ComplianceSOC 2

Tech Stack

Tools & technologies

AirflowApacheAWSCloudDistributed SystemsKafkaTerraform

About the role

Key responsibilities & impact

Design, build, and operate distributed services and compute infrastructure for the data platform, including containerized workloads on AWS ECS, autoscaling, resource sizing, and orchestration
Own end-to-end design and development of scalable data pipelines and data-moving services from ingestion and orchestration through transformation and delivery
Improve movement of event-sourced data from production systems into data infrastructure and back to other systems
Participate in on-call for the data platform and own production issues in distributed data systems end to end
Secure participant and employer data through PII classification and masking, role-based access controls, least-privilege patterns, encryption, key management, lineage, and audit trails supporting SOC 2 and regulatory obligations
Lead technical direction and evolution of the data platform toward AI-first infrastructure, including AI consumption, unstructured data access, AI tooling, and production model and AI workloads
Build interfaces for data engineers, analysts, and AI systems, and systems that move curated data from the warehouse into production services and downstream tools
Mentor engineers and analysts and raise standards for testing, code review, and operational readiness

Requirements

What you’ll need

5+ years of experience building and operating production software systems, with significant experience in data-intensive systems such as data pipelines, data streaming platforms, and data infrastructure
Experience designing distributed systems and services, including concurrency, backpressure, idempotency, partial failure, and related tradeoffs
Hands-on experience running containerized workloads in production on AWS, including scaling, resource sizing, and performance and cost tuning under real load
Ability to independently own and improve complex production systems
Experience with 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 desire to leverage AI tools and workflow automation as the primary way work gets done
Preferred: hands-on experience with event-sourced or append-only log systems, change data capture, or streaming platforms such as Kafka or Kinesis
Preferred: working knowledge of cloud data warehouses such as Snowflake, including access control, performance tuning, and cost management
Preferred: experience deploying and operating machine learning models in production
Preferred: experience with data lakehouse architectures and open table formats such as Apache Iceberg or Delta Lake
Preferred: experience building data infrastructure for AI-driven data access, including MCP, AI data governance, and evaluation of AI-generated query responses
Preferred: background in fintech, financial services, or another regulated or compliance-driven industry

Benefits

Comp & perks

401(k) plan with dollar-for-dollar employer match up to 4% of compensation, immediately vested, with $0 plan fees
Top-of-the-line health plans, dental insurance, and vision insurance
Competitive time off and parental leave
Addition Wealth: Unlimited access to digital tools, financial professionals, and a knowledge center supporting financial wellness
Lyra enhanced mental health support for employees and dependents
Carrot fertility healthcare and family-forming benefits
Candidly student loan resources
Monthly work-from-home stipend
Quarterly lifestyle stipend
Team-building experiences, including virtual social events and team offsites
Additional compensation components such as bonuses, commissions, and equity may be offered
Physical, financial, and mental wellness benefits