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Senior Backend Engineer, Data PlatformiTCO Solutions • United States
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Senior Backend Engineer, Data Platform

iTCO Solutions
  • US
    United States
  • US
    United States
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Über

Senior Backend Engineer
100% remote until the New York City office opens, as the team scales and becomes fully operational. What this role is about We are looking for a Senior Backend Engineer with strong data systems experience to take ownership of the backend services and data workflows that power Splink's core product. You will work closely with the founders to strengthen the architecture, reliability, and operational maturity of systems that ingest, reconcile, transform, and serve complex retail and trade-promotion data. This role is backend-first and highly execution-focused. You will design and ship production services, improve application and data-model correctness, strengthen asynchronous workflows and pipeline reliability, and help evolve the system for higher scale and customer complexity. The ideal candidate is deeply comfortable building backend systems, but also has strong experience with data pipelines, operational data quality, and the realities of messy real-world data. What you'll do Own backend systems and data workflows Design, build, and operate backend services and supporting data workflows that power ingestion, reconciliation, product logic, and internal operations. Design reliable asynchronous processing Build and maintain batch and near-real-time workflows with strong attention to idempotency, replay safety, schema evolution, and safe backfills. Model and serve operational data correctly Design application and analytical data models that support correctness, performance, and maintainability across customer-facing and internal use cases. Improve database performance and reliability Optimize query patterns, indexing, partitioning, and data access paths as data volume and customer complexity grow. Strengthen observability and operational maturity Improve logs, metrics, tracing, alerting, runbooks, and incident response so production issues are easier to detect, diagnose, and resolve. Establish data quality and freshness protections Implement validation checks, freshness monitoring, and operational safeguards to catch correctness issues early. Make pragmatic architectural decisions Balance speed, maintainability, and operational risk while evolving the current system toward higher scale and reliability. Collaborate across codebases and teams Work closely with founders and the offshore team on shared services, integrations, debugging, and knowledge transfer. Ship customer-impacting improvements Use trusted data to enable product capabilities, reduce operational toil, and improve the consistency of customer-facing workflows. What we're looking for in our ideal candidate 5+ years of experience in backend, platform, or data-intensive software engineering Strong experience building and operating production backend systems Strong experience with Python or TypeScript, plus strong SQL skills Strong experience designing and operating production data workflows, including ingestion, transformation, reprocessing, and schema changes Deep experience with relational databases, especially schema design, query performance, and data modeling tradeoffs Experience building reliable systems with testing, monitoring, alerting, and debugging in production Experience working in AWS environments Ability to make pragmatic technical decisions that balance speed, correctness, and operational risk Strong ownership and communication skills in a small, fast-moving team Comfort working across backend services, operational data, and ambiguous problem spaces We do not expect you to have experience in every area listed. If this role excites you and you believe you can grow into it, we encourage you to apply. Nice-to-have experience (not required!) Experience building data-intensive backend systems in small, fast-moving teams Experience with event-driven or queue-backed workflows Experience with distributed systems observability and tracing. Experience with customer-facing platforms where data correctness directly affects product behavior Experience with machine learning operations, model-serving infrastructure, or production support for machine learning systems. This should stay a bonus, not a requirement. Experience with Dagster or Apache Airflow, especially around safe backfills, idempotent workflows, and production debugging. Our stack Data platform
Language: Python Adjacent systems: Frontend Language: TypeScript Frameworks: Next.js, React Styling: Tailwind, Sass Backend Language: TypeScript Frameworks: Node.js, Express.js Data: PostgreSQL, Sequelize (ORM) Caching: Redis Benefits include: Flexible paid time off A holiday schedule aligned with standard US holidays Sizable equity in the company, typically between 0.5% - 1%
  • United States

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  • English
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