Our client, Gieni AG is a fast-growing B2B AI software company based in Zurich and closely connected to the Microsoft ecosystem. Its platform uses AI agents to automate complex business processes end-to-end. By combining advanced data engineering, AI-driven classification, and semantic search, Gieni helps organizations identify opportunities faster, improve targeting, and make smarter commercial decisions.

About the Role

As a Senior Data Engineer you will own the data pipelines and infrastructure behind Gieni Explorer — a large-scale intelligence platform covering 6.5M+ companies across 150+ countries.

This is a high-impact role at the core of the product. You will design and scale the systems that power real-time ABX (Account-Based Execution) workflows, ensuring data is accurate, fresh, and reliable at all times.

This is not just about building pipelines — it’s about owning data quality and turning it into a competitive advantage.

Why Join

• Own a critical product layer — not just infrastructure support
• Work with large-scale, global datasets in a fast-evolving environment
• Operate at the intersection of data engineering and AI
• High level of autonomy and technical ownership
• Direct impact on systems used in real-time decision-making

What You’ll Do

• Own the end-to-end data ingestion pipeline: crawling, parsing, classification, and entity resolution
• Ensure data quality, freshness, and lineage, with monitoring that detects issues before customers do
• Design and maintain data interfaces and APIs used by ABX systems at runtime
• Build and evolve Azure-based data architecture, including Data Lake, Synapse/Databricks, Functions, and streaming
• Develop and operate embedding pipelines and vector stores
• Collaborate closely with Data Science on semantic search, classification, and AI-driven systems

What We’re Looking For

Required

• 5+ years of experience in data engineering, working with production-scale systems
• Strong Python and SQL skills
• Experience with distributed data processing frameworks (e.g. Spark, Flink, Beam)
• Hands-on experience with cloud data platforms (Azure preferred)
• Practical experience with embedding pipelines or vector databases
• Strong ownership mindset with a focus on data quality and reliability

Preferred

• Experience with B2B data products or market intelligence platforms
• Familiarity with knowledge graphs or graph databases
• Experience working alongside data scientists on ML or embedding systems in production

Interested? Apply with your profile, or reach out for a confidential first conversation — we’re happy to tell you more.