Job Opportunities API

Multiverse Computing Multiverse is a well-funded, fast-growing deep-tech company founded in 2019. We are the largest quantum software company in the EU and have been recognized by CB Insights (2023 and 2025) as one of the 100 most promising AI companies in the world. With 180+ employees and growing, our team is fully multicultural and international. We deliver hyper-efficient software for companies seeking a competitive edge through quantum computing and artificial intelligence. Our flagship products, CompactifAI and Singularity, address critical needs across various industries: CompactifAI is a groundbreaking compression tool for foundational AI models based on Tensor Networks. It enables the compression of large AI systems—such as language models—to make them significantly more efficient and portable. Singularity is a quantum- and quantum-inspired optimization platform used by blue-chip companies to solve complex problems in finance, energy, manufacturing, and beyond. It integrates seamlessly with existing systems and delivers immediate performance gains on classical and quantum hardware. You’ll be working alongside world-leading experts to develop solutions that tackle real-world challenges. We’re looking for passionate individuals eager to grow in an ethics-driven environment that values sustainability and diversity. We’re committed to building a truly inclusive culture—come and join us. Responsibilities · Own the end-to-end design and delivery of data platform architectures — lakehouse, data catalog, and governance — from initial scoping through production release · Design, implement, and operate large-scale ETL/ELT pipelines and workflow orchestration to ensure data is clean, accurate, versioned, and accessible · Define data modeling, partitioning, schema evolution, and versioning conventions so datasets remain queryable, interoperable, and reproducible at scale · Establish and maintain authoritative data catalogs, including schemas, metadata, lineage, sensitivity labels, and access policies · Validate released datasets against their sources for completeness, correctness, schema consistency, and query performance, defining objective acceptance criteria · Work closely with Machine Learning and AI Engineers to make data products directly consumable by analytics, APIs, and AI/agent workflows · Collaborate with clients and cross-functional teams to scope requirements, lead technical sessions, and document architectures for knowledge transfer and internal ownership · Mentor and support other data engineers, reviewing designs and code and raising the team's engineering standards · Stay up to date with emerging trends in data engineering — open table formats, data catalogs, orchestration — and drive their adoption where they add value Required qualifications: · Bachelors or master's degree in computer science, software engineering, or a related field · 5+ years of professional experience in data engineering, including ownership of production data platforms or pipelines · Expert programming skills in Python and strong command of SQL · Expertise in data modeling, ETL development, and database management, with both SQL and NoSQL databases · Hands-on experience with lakehouse architectures and columnar / open table formats (e.g., Parquet, Apache Iceberg, Delta Lake) · Experience with distributed data processing frameworks such as Spark, and with workflow orchestrators such as Airflow or Argo Workflows · Strong experience with cloud data platforms (Azure, AWS, or GCP), including object storage, containers, and Kubernetes · Solid grounding in data governance: catalogs, metadata, lineage, access control, and dataset versioning · Comfortable with Git-based workflows, CI/CD, and infrastructure-as-code working models · Excellent problem-solving, communication, and collaboration skills; able to lead technical discussions wi