Backend Engineer - Data & Orchestration
- Remote
- All software engineering jobs
- Berlin
- FullTime
- Technology
About the role
Who we are
Melotech is revolutionizing media and entertainment. We create art through technology for humans to enjoy. In just 24 months, our work has been heard, watched and loved for over 3 billion minutes worldwide.
Founded by entrepreneur and investor Soheil Mirpour, we are backed by top VCs Cherry Ventures, Speedinvest and GFC, alongside world-class angels from firms such as Spotify, Blackstone and KKR.
What you will do
Everything we ship runs on data, and the systems that collect, move and store that data need an owner. As Backend Engineer - Data & Orchestration, you take a data platform that grew fast and turn it into one system the whole company can rely on. You keep it running, you keep it clean, and you make it simpler every month. This is not a pure ETL or warehouse role: you work across the pipelines and the backend services they depend on. We will walk you through exactly what we are building as you go through the process. On a typical day, your tasks may include:
Data collection: keeping our scrapers and platform integrations running across flaky sources, rate limits, anti-bot measures and APIs that change overnight
Pipelines and storage: owning our event-driven pipelines end to end, from orchestration (Airflow, Dagster or similar) to databases and warehouses, built to survive failures and to keep costs in check
Monitoring and reliability: building the monitoring and alerting (Datadog or similar) that keeps our services and integrations healthy, and the checks on freshness, volume, schema and values that catch a wrong number before anyone downstream notices
Backend services: working on the production services and APIs our data flows through, including our JavaScript backends
Infrastructure and security: owning CI/CD, infrastructure as code and cloud for our data systems, plus access and secrets: who and what can reach which system, including AI tools
Simplification: consolidating what grew fast into one documented system, and removing what is no longer needed
Working across the team: explaining what the data can and cannot do to non-technical colleagues, and guiding junior engineers as the team grows
Who you are
We are looking for an engineer who runs what they build, and builds things that keep running. You have operated real production systems in a small, fast-moving company, and people trust you with them.
Typically, your profile will look like this:
Experience: 3 to 10 years of hands-on engineering, most of it in small or fast-growing companies where you owned production systems yourself rather than handing them to a platform team
Python and backend: advanced Python, including async code and long-running data jobs, and enough backend experience to work on production services and APIs, including basic JavaScript or TypeScript backends
Scraping and data acquisition: you have kept unreliable external sources running in production (scrapers, platform APIs, unofficial endpoints) and you know how to handle proxies, rate limits and anti-bot measures; using LLMs to extract data from messy sources is a plus
Pipelines and storage: you have designed and run event-driven, fault-tolerant pipelines handling millions of records a day, with Airflow, Dagster or task queues, on databases such as Postgres, ClickHouse, MongoDB or Redshift, and you know what they cost to run
Data reliability and monitoring: your systems report their own problems through freshness, volume, schema and value checks, and you use Datadog or an equivalent to keep services and integrations reliable, because a wrong number that nobody noticed is the outcome you design against
Infrastructure and security: you are comfortable with Docker, Terraform, CI/CD and cloud, and ideally you have run an access review and set up role-based access and secrets management
Ownership and communication: you have owned a messy data setup end to end at a smaller company and left it simpler, documented and maintainable; you explain trade-offs to non-technical colleagues, push back when it matters, and have guided junior engineers or led a small team
Engineering fundamentals: you learned to build solid systems before AI coding tools were everywhere, and today you use them to go faster, not to replace that judgment; you ship fast, keep the codebase clean, and take the time to understand the context before you build
Pace: you thrive in a fast-paced and performance-oriented environment
What makes this exciting
Our data systems feed everything the company does, and you own them outright. You are not maintaining someone else's legacy: you decide how these systems should work and you make them work that way. You're not a cog in the machine but the captain of your own ship, rewarded for performance and respected for leadership. Flat hierarchies mean that your voice matters, your ideas get implemented, and your impact is immediate.
We pay competitive salaries and make you an owner of the business with equity. We work remotely to give you complete freedom over your life, while meeting regularly around the world for global offsites where we strategize, bond, and push boundaries together.
What the process will look like
We hire on a rolling basis. Earliest starting date is always ASAP.
Once you begin our process, you can progress from start to offer within a week, depending on how quickly you can move through each stage:
Initial interview: 30-minute introductory call - getting to know you
Case interview: 90-minute case discussion - present and debate your skills
Founder interview: 90-minute interview with our CEO - going deep on all topics
Offer, contract signing and onboarding
Note: As we are still in stealth, you will learn more about Melotech as you progress through the stages. By the end of the Founder interview, you will have a full grasp of our business and the details of your role.
Description as published by Melotech.