Backend Engineer - Data & Orchestration

Meyandy LLC; Berlin; Hybrid; EUR 90.000 - 150.000; Vollzeit

Zusammenfassung

Melotech is seeking a Backend Engineer - Data & Orchestration to own and evolve a data platform used across the company. You will work on data collection, pipelines, and backend services, ensuring reliability and scale in a fast-growing environment.

Qualifications include 3–10 years of hands-on engineering, strong Python backend skills, and experience with scraping, pipelines, and monitoring tools. Berlin-based, on-site role with modern cloud practices.

Qualifikationen

• 3–10 years of hands-on engineering in startup-like environments.

Aufgaben

• Own data collection, pipelines, and storage end-to-end.
• Maintain production services and APIs used by data flows.
• Ensure security, access control, and Secrets management.
• Collaborate with non-technical teams to explain data capabilities.
• Implement checks for data freshness, volume, and schema.

Kenntnisse

Python

Backend development

Async IO

Scraping

Data pipelines

Postgres

Airflow

Dagster

Datadog

Docker

Terraform

CI/CD

Cloud

Tools

Postgres

ClickHouse

MongoDB

Redshift

Airflow

Dagster

Datadog

Docker

Terraform

Jobbeschreibung

# Backend Engineer - Data & OrchestrationMelotechVia arbeitnowBerlin, DEPubliée il y a 6h## Description du poste**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 ...