Backend Engineer, Data & Orchestration

• 3-10 years of hands-on engineering experience, primarily in startups or high-growth companies.\n
• Advanced Python skills, including asynchronous code and long-running data jobs.\n
• Backend experience building and maintaining production services and APIs, plus familiarity with JavaScript or TypeScript backends.\n
• Experience operating unreliable external data sources, including scrapers, platform APIs, or unofficial endpoints, with knowledge of proxies, rate limits, and anti-bot measures.\n
• Experience designing fault-tolerant, event-driven pipelines processing high data volumes, using Airflow, Dagster, task queues, or similar tooling.\n
• Familiarity with databases and warehouses such as Postgres, ClickHouse, MongoDB, or Redshift, including performance and cost considerations.\n
• Strong monitoring and data-reliability practices, using Datadog or comparable tools and implementing meaningful quality checks.\n
• Comfort with Docker, Terraform, CI/CD, cloud infrastructure, role-based access control, and secrets management.\n

n We are a fast-growing, venture-backed technology company operating at the intersection of media, entertainment, and consumer growth. We use technology and data to create, distribute, and scale content for global audiences, with products that have already reached significant engagement at scale. \n

\n The team combines an entrepreneurial operating model with deep expertise across consumer technology, growth, data, and creative production. We are building quickly in a large and evolving market, with a high bar for ownership, experimentation, and measurable outcomes. \n

\n What you will do \n The company’s products and decisions depend on reliable data systems. As a Backend Engineer focused on Data & Orchestration, you will take ownership of a rapidly evolved data platform and turn it into a dependable, documented, and scalable system. \n

\n This is not solely an ETL or warehouse role. You will work across data pipelines, production backend services, infrastructure, and the integrations that support them. \n

\n Typical responsibilities include: \n \n

• Keeping scrapers and third-party platform integrations operational despite unreliable sources, rate limits, anti-bot measures, and changing APIs.\n
• Owning event-driven data pipelines end to end, from orchestration tools such as Airflow or Dagster to databases and warehouses.\n
• Building monitoring, alerting, and data-quality checks for freshness, volume, schema, and values.\n
• Contributing to production backend services and APIs, including JavaScript or TypeScript services.\n
• Managing CI/CD, infrastructure as code, cloud systems, access controls, and secrets for data infrastructure.\n
• Consolidating fragmented systems into a simpler, documented, maintainable architecture.\n
• Communicating data capabilities and limitations to non-technical colleagues and mentoring junior engineers as the team grows.\n

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\n Who you are \n You are an engineer who takes ownership of production systems from design through day-to-day operation. You have worked in a small or fast-moving environment where you were trusted to build and run critical infrastructure. \n, * A record of simplifying and documenting a messy data environment, communicating trade-offs clearly, and supporting more junior engineers.\n

• Strong engineering fundamentals, sound judgment, and effective use of modern AI coding tools.\n
• Comfort operating in a fast-paced, performance-oriented environment.\n

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\n What makes this exciting \n You will own data systems that underpin the company’s core operations and have substantial influence over how they evolve. This is an autonomous role with the opportunity to improve reliability, reduce complexity, and establish the foundations for future scale. \n

\n The company offers competitive compensation, equity, remote flexibility, and periodic in-person team offsites.