Senior Data Engineer | VC-Backed Scale-Up | Databricks, PySpark & Modern Lakehouse | Berlin (On[…]

AI Futures have partnered with a recently Series A–funded B2B SaaS company to hire a Senior Data Engineer.

The business is building a next-generation data and workflow platform for large, operationally complex industries that have historically been underserved by modern software. Operating in a multi-trillion-dollar global market, the company enables traditional enterprises to unlock the full value of their data through advanced analytics, machine learning, and intelligent automation.

Its platform integrates real-time analytics, predictive modelling, and workflow automation into a single, customer-facing application used directly by senior decision-makers to modernise operations and drive measurable commercial impact. The Role

As a Senior Data Engineer, you will play a foundational role in building and owning the company’s modern data platform. You will design and scale the lakehouse architecture that powers real-time analytics, embedded data products, and machine learning applications.

You will: • Design, build, and maintain scalable ETL/ELT pipelines across diverse structured data sources • Develop real-time and batch data pipelines powering ML models and operational dashboards • Create flexible, scalable data models to support customer-specific datasets • Write and optimise high-performance transformations within a modern lakehouse environment • Own and configure the Databricks platform (Delta Lake architecture) • Partner closely with Data Science, Product, and Engineering to translate business requirements into robust data solutions • Improve reliability, performance, and cost-efficiency across the AWS data stack • Establish best practices in data modelling, testing, and platform governance • Contribute to CI/CD and strong software engineering standards within the data environment The Candidate

You are a hands-on, product-minded data engineer who enjoys building scalable, production-grade data systems in high-growth environments.

You bring: • 3+ years of experience in Data Engineering, Analytics Engineering, or backend-focused data roles • Strong Python and SQL skills, including advanced query optimisation • Solid experience building ETL/ELT pipelines using PySpark and orchestration tools (e.g., Airflow) • Hands-on experience with modern data warehouses/lakehouses (e.g., Databricks, Snowflake) • Experience with data transformation tooling such as dbt • Strong understanding of data modelling principles for analytics and customer-facing applications • Familiarity with AWS cloud infrastructure • A solid grasp of software engineering best practices in data environments • Interest in how analytics and ML power product features • Exposure to MLOps concepts is a plus • An experimental, fast‑iteration mindset suited to startup environments • Strong communication skills and comfort working cross‑functionally

Experience in high-growth tech or venture‑backed environments is a plus. Why This Role • Opportunity to shape the data backbone of a category‑defining B2B SaaS platform • High ownership with architectural impact from day one • Work closely with experienced operators from top‑tier tech and consulting backgrounds • Build data products used directly by C‑suite leaders in large industrial businesses • Backed by leading international VCs • Fast‑growing Berlin‑based scale‑up environment

If you’re excited about building real‑time data infrastructure that directly powers AI‑driven products in a massive, under‑digitised global industry, this is a rare opportunity to join at the foundation stage and make a lasting impact.

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Salary: EUR 48000 - 84000 per year