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 RoleAs 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 environmentThe CandidateYou 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-functionallyExperience 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 environmentIf 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.