AI - Data Engineer

About The Role

We are looking for a Senior Data / AI Engineer to design, build, and scale modern data platforms and AI-driven solutions. You will operate at the intersection of data engineering, analytics engineering, and applied AI - leveraging robust data pipelines and transformation workflows to enable advanced analytics, machine learning, and emerging AI agent use cases.

This role is especially well-suited for someone with a strong consulting background who is comfortable working in client-facing environments, translating ambiguous business requirements into structured, production-ready data and AI solutions.

Do you want the unique possibility to invest in the next generation of tech startups while building large-scale solutions for mid-to-large enterprises?

Then VNTRS might be the right fit for you!

Location: Stockholm (Onsite/Hybrid)

Your Impact: Builder & Investor

At VNTRS, you are more than an engineer; you are a builder and an investor.

Ownership & Equity: We combine the impact of high-level consulting with the strategic upside of venture capital. Through our unique model, you gain ownership in the companies we support, becoming a shareholder in our diverse portfolio of over 35 ventures.

The Investment Council: You’ll have the opportunity to join our Investment Council and help decide which startups we back next.

AI Strategy & Workshops: Beyond pure engineering, you will help our internal AI Forum on the business side - conducting workshops and identifying AI possibilities for our mid-to-large size clients.

The Role: Tech & Innovation

You will join a collaborative group of experts dedicated to high-quality code and modern solutions. In this role, you will bridge the gap between Software Engineering and Advanced Data Science.

Technical Requirements

Must-haves

• Consulting Experience: 6-7+ years of experience in data engineering or analytics engineering, with a strong track record in consulting, professional services, or client-facing project work. Proven ability to manage stakeholder expectations and deliver solutions in dynamic environments.
• Expert-level dbt: Deep experience in modular data modeling, including macros, custom materializations, and version-controlled SQL.
• Production-grade Python: Ability to write clean, reusable code (not just scripts) using testing frameworks like pytest and dependency management.
• Modern Cloud Warehousing: Senior-level expertise in BigQuery or Snowflake, with a strong focus on architecture and performance optimization.
• Data Engineering Best Practices: Experience implementing CI/CD for data, data quality monitoring, and automated testing.

Preferred Skills

• AI & LLM Foundations: Experience with Vector Databases (e.g., Pinecone, pgvector) and building data pipelines for RAG (Retrieval-Augmented Generation).
• Advanced Orchestration: Hands-on experience with Airflow, Dagster, or Prefect for complex workflow management.
• Distributed Processing: Experience with Apache Spark (PySpark/Scala) for handling large-scale, decentralized data.
• FinOps Mindset: A track record of monitoring and optimizing cloud compute costs and warehouse spend.
• MLOps: Familiarity with Vertex AI or similar platforms for managing the machine learning lifecycle.
• Semantic Layer: Experience defining metrics and business logic via the dbt Semantic Layer or MetricFlow.

Culture & People

Our culture is built on our values: Adventurous, Caring, and Inspiring.

• Community: We are a dog-friendly office (Barkend developers welcome!) that loves spending time together through Hackathons, After Works, and communal lunches.
• Balance: We respect that everyone is in different stages of life. Your well-being and work-life balance are top priorities.
• Growth Mindset: You own your trajectory: we simply provide the space and resources for you to master new tech, sharpen your business acumen, and evolve far beyond just your technical field.

Ready to build the future of AI and data with us?