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# Senior Software Engineer - Backend, Data Products - MarTech/AdTech

- **Company:** Three Pillars
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), C++ (Programming Language), Data Validation, Extract Transform Load (ETL), Python (Programming Language), PostgreSQL, Query Optimization, Software Engineering, SQL Databases, SQLAlchemy, Management of Software Versions, Great Expectations (Foster Youth College-readiness and Support Program), AI Coding Agents, Backend, Pandas, Apache Kafka, Apache Nifi, Graphql, Data Pipelines
- **Published:** November 4, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-software-engineer-backend-data-products-martech-adtech-san-francisco-ca--0e7db8c0-1bce-46c4-8ba9-719fa0a76d7a

## About the Role

Software Engineering, Adtech, Machine Tool, Software Engineering, GraphQL, Product Development, Transformation Tools, Marketing, Data Quality, Analysis Skills, Engineering fundamentals

 * 5+ years writing production software, with deep Python (3.10+, async/await, type hints; pandas, SQLAlchemy, Pydantic).
 * Built resilient, observable ETL/ELT pipelines that ingest, transform, and validate data at scale.
 * API/backend design: GraphQL and/or REST contracts, versioning, and ergonomics other engineers actually enjoy using.
 * PostgreSQL depth - schema design, query optimization; comfortable with both ORM and raw SQL.

Systems & tooling

 * Event-driven and workflow-orchestrated systems (Temporal, NATS / Kafka, or similar).
 * Data validation / quality frameworks, and a habit of designing for correctness and debuggability.

Nice to have

 * Plugin / extension development (Apache NiFi or similar) and fluency with AI coding assistants as part of your workflow.
 * Performance-sensitive work in a systems language (Rust, C++); graph / lineage modeling; connector ecosystems.

## Description

As a Senior Software Engineer on Backend, Data Products, you build the product itself - the composable, self-correcting pipeline capabilities customers actually use. You develop Reactors (the Observe / Match / Act / Compose primitives at the heart of the platform), the connectors and tooling that bring messy real-world data in, the validation that keeps it trustworthy, and the backend/GraphQL surface that exposes it. This is applied backend engineering: turning a hard product vision into resilient, shippable features.

What You'll Do

 * Build and extend Reactors - the Observe / Match / Act / Compose primitives that make pipelines composable and self-correcting.
 * Develop connectors, ingestion, and transformation tooling for diverse, messy marketing data sources, including schema evolution.
 * Build data validation and quality into the pipeline (e.g., Great Expectations-style contracts) so correctness is enforced, not hoped for.
 * Design and ship the backend / GraphQL surface that exposes pipeline capabilities to internal teams and customers.
 * Orchestrate multi-step pipeline work with workflow engines (Temporal) and event-driven dispatch (NATS/JetStream).
 * Collaborate in a sprint-based cycle with product and science to turn analytical workloads into production features.