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Open nowPosted 246 days ago

Senior Backend Engineer - Data Platform (m/f/d)

Blocks8 open roles

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Your applicationOpen nowSenior Backend Engineer - Data Platform (m/f/d)Blocks

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7.4% of postings close within 7 days. Measured by our own scanner across the market.

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  2. 3.5%3 days
  3. 7.4%7 days
  4. 13.2%14 days
  5. 34.6%30 days
This job: posted 246 days ago

The posting

Who we are

BLOCKS is bringing big-company cloud efficiency to startups and SMEs. We guarantee 20% savings from day one by pooling cloud spend into a group-buying model. From there, our AI agent “Major Tom” acts like a virtual DevOps engineer, finding waste, optimizing infrastructure, all in an automated way to maximize cloud efficiency. And this is just the beginning, more to follow in our discussion with you.

Our founders (Oliver and Andreas) are serial entrepreneurs, have raised >$1 billion, and successfully sold multiple businesses.

Your role

You'll architect and build the core backend systems powering our cloud cost optimization platform from day zero. You'll design the multi-tenant database architecture, develop high-performance APIs in Python and FastAPI, and design the AWS ETL pipelines that transform billing and usage data into structured cost insights for automated savings plan management.

Your immediate focus: Build the backend for our 1-click AWS connection flow, design the database schema for multi-tenancy (SQL + Iceberg), and create the API architecture serving our web dashboard. You'll also develop the backend logic for our AI DevOps agent “Major Tom,” including automated server scheduling, cost anomaly detection, and AWS invoice processing using Airflow, PySpark, and Trino.

As one of our founding engineers, you'll own critical architectural decisions that scale from startup to enterprise. You'll work directly with AWS APIs, define a high-coverage testing framework, and implement CI/CD from day one to enable rapid iteration, seamless deployment, and high uptime.

What you bring

  • Deep expertise in Python and FastAPI: You have built and operated production-grade systems end-to-end with clean, maintainable architecture
  • Strong background in data processing and orchestration: You are hands-on with Pandas, PySpark, Airflow, and Trino for large-scale distributed data workflows
  • Proven ability to design, optimise, and scale data infrastructure: You have architected SQL databases and Iceberg-based data lakes for performance, reliability, and cost efficiency
  • Strong AWS experience: You know CloudFormation, cross-account IAM roles, billing/cost APIs, and automated infrastructure workflows by heart
  • Led system design and delivery: You have mentored peers, reviewed designs, and driven architectural decisions for scalable, maintainable services
  • Startup execution mindset: You have shipped 0→1 products fast with high ownership, autonomy, and accountability
  • Curious, pragmatic problem solver: You experiment quickly, learn deeply, and optimise for impact over theory
  • Direct communicator: You value clarity and feedback as tools for speed, improvement, and alignment
  • Demonstrated impact: You have impressive achievements from previous jobs and from side projects. Please share them with us.

What we offer

  • Build where AI actually matters. Real AI shipped into production that changes how companies run cloud infrastructure.
  • Work with founders who’ve done it before. Unicorn builders, $1B+ raised, zero politics, fast calls, radical candor. We move, not debate.
  • Zero to One. The opportunity to build a product which startups will consider standard infrastructure.
  • Real ownership, not theater. We challenge, you make calls. Some will be wrong. That’s fine. We fix fast and keep shipping.
  • Compensation that reflects ambition. Top market cash compensation plus meaningful equity upside.
  • Berlin, in person, by design. Early stage companies are built together, not on Zoom. We support relocation.

How we hire

We believe hiring should be like we build: Fast, respecting your time and ours, to the point:

  • Intro call with a founding team member (30 min)
  • Tech interview/assessment with an engineer (~60 min)
  • In-person tech case study with founders and engineers (1-2 hours)
  • Offer call within 24 hours with a founder (15 min)
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