Careers

About the Role

We're looking for a US based backend engineer to work across our data pipeline, infrastructure, and deployment systems. You'll build and maintain the services that power our Customer Data Platform - from ingestion workflows that resolve millions of customer profiles, to the infrastructure that keeps it all running on AWS.

This isn't a single-repo job. You'll move between our Python data platform, Terraform infrastructure, and Kubernetes deployment manifests depending on what the work demands.

What You'll Work On

• Data Pipeline Development - Build and extend Temporal workflows for data ingestion, audience segmentation, and profile resolution in Python 3.12 / FastAPI
• Infrastructure as Code - Provision and maintain AWS resources (EKS, RDS, S3, IRSA) using Terraform, deployed via Terraform Cloud
• Deployment & GitOps - Manage Kustomize manifests and ArgoCD-driven deployments to EKS, including sync-wave orchestration for zero-downtime releases
• Cross-Service Integration - Work at the boundaries between services - API contracts, event-driven workflows, and shared infrastructure dependencies
• Observability - Instrument services, investigate production issues, and improve monitoring across the platform

What We're Looking For

Must-Have

• 3-5 years backend engineering experience
• Strong Python - you've built production services, not just scripts
• Relational database experience (PostgreSQL preferred) - schema design, migrations, query optimization
• Comfort with REST API design and async patterns
• Familiarity with containerized deployments (Docker, Kubernetes basics)
• Git workflow proficiency - you work in PRs, understand branching strategies

Strong Preference

• Temporal or similar workflow orchestration (Airflow, Step Functions, Prefect)
• Terraform or equivalent IaC tool - you've written modules, not just run applies
• AWS services experience (EKS, RDS, S3, IAM/IRSA, Secrets Manager)
• Kustomize or Helm for Kubernetes configuration
• FastAPI or similar async Python web framework
• SQLAlchemy (async) and Alembic migrations

Nice to Have

• ArgoCD / GitOps deployment patterns
• Meltano / Singer ecosystem (ELT pipelines)
• Multi-tenant SaaS architecture experience
• CI/CD pipeline design (GitHub Actions)
• Experience with External Secrets Operator or similar secrets management

We need a US based senior backend engineer who can own systems end-to-end - from designing Temporal workflow architectures that process millions of customer profiles, to provisioning the AWS infrastructure underneath them, to ensuring the GitOps deployment pipeline delivers it all reliably.

You'll be the person who understands how a schema change in PostgreSQL ripples through FastAPI services, affects Kubernetes manifests, and requires coordinated Terraform updates. You'll make those cross-cutting decisions with confidence because you've been burned by the alternative.

What You'll Own

• Data Platform Architecture - Design and evolve Temporal workflow patterns for ingestion, audience segmentation, profile resolution, and sequencing. Make decisions about retry strategies, idempotency, and failure isolation across 15+ workflow types
• Infrastructure Design - Architect and maintain multi-account AWS infrastructure (dev/global/prod) via Terraform Cloud - EKS clusters, RDS instances, IRSA policies, networking, and secrets management. You understand that this layer has the highest blast radius in the system and you treat it accordingly
• Deployment Pipeline Ownership - Own the GitOps flow: GitHub Actions to ECR to ArgoCD to EKS. Design sync-wave orchestration (DB to migrate to app to schedules) and ensure zero-downtime deployment guarantees hold under real conditions
• Cross-Service Contracts - Define and enforce API boundaries between services. Our data platform handles 22+ API endpoints consumed by the core API, plus reverse callbacks - you'll keep those contracts stable as both sides evolve
• Platform Reliability - Drive observability, incident response, and capacity planning. When something breaks at 2am, the deployment chain and infrastructure decisions you made determine whether it's a 5-minute fix or a 5-hour outage
• Technical Leadership - Review PRs with an adversarial eye for cross-repo impact. Mentor mid-level engineers. Make build-vs-buy decisions. Push back on complexity that doesn't earn its keep

What We Expect

Required

• 5-10 years backend engineering, with at least 2 years owning production infrastructure
• Deep Python expertise - you've designed service architectures, not just written endpoints
• PostgreSQL at depth - partitioning strategies, migration safety, connection pooling, query plans, not just ORMs
• Production Kubernetes experience - you've debugged pod scheduling, resource limits, networking issues, and lived to tell the story
• Terraform in anger - you've written modules, managed state, handled drift, and know when to import vs recreate
• AWS fluency - EKS, RDS, S3, IAM/IRSA, ALB, Route53, Secrets Manager as tools you reach for without documentation
• Strong opinions on API contract design, versioning, and backward compatibility - informed by experience breaking things
• You've operated multi-service systems where a change in one repo requires coordinated changes across others

Expected

• Temporal or comparable workflow orchestration at scale (Cadence, Step Functions) - you understand deterministic execution constraints, activity retry semantics, and workflow versioning
• ArgoCD / GitOps patterns - you've designed deployment pipelines, not just consumed them
• Kustomize overlays for multi-environment configuration management
• Multi-account AWS architecture - organizational SCPs, cross-account IAM, centralized ECR/OIDC
• FastAPI or similar async Python frameworks with SQLAlchemy async and Alembic
• CI/CD pipeline design with GitHub Actions - build, test, push, deploy as a coherent system

Differentiators

• Meltano / Singer ecosystem experience (ELT pipeline orchestration)
• External Secrets Operator or similar Kubernetes-native secrets management
• Terraform Cloud workspace design and workspace-to-environment mapping
• Multi-tenant SaaS - tenant isolation at the data layer, not just the application layer
• You've built or significantly evolved a developer platform or internal tooling