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.