IQM is a global leader in designing, building, and selling superconducting quantum computers. IQM provides both on-premises full-stack quantum computers and a cloud platform to access its computers anywhere in the world. IQM customers include the leading high-performance computing centres, research labs, universities and enterprises which have full access to IQM's software and hardware. IQM has over 300 employees with offices in Finland, Germany, France, Spain, Poland, Singapore and the US.
At IQM, we work with sensitive data and strong security requirements. For that reason, our data services and tooling run on premises. In this role, you will build and improve production grade data solutions that teams can rely on every day. You will help us use data more effectively across the company by raising the quality and usability of our pipelines, models, and datasets. You will also guide engineering best practices in the team, and bring clarity when multiple teams need to align.
What will I be doing?
Extend the responsibilities of an intermediate data engineer, with a strong focus on quality, scalability, and long term maintainability
Improve, manage, and advise on standards for code maintainability and performance across the data codebase
Implement and review code for data pipeline design, considering downstream utility and performance (for example Tableau, ML models, and internal stakeholders)
Create architecture recommendations and implement them hands on
Take ownership of initiatives that improve data utilization, data efficiency, and data trust across the company
Share knowledge and raise the bar for data engineering practices through coaching, reviews, and clear documentation
Build alignment across teams by communicating clearly and helping people reach consensus
Support hiring by performing technical interviews and contributing to a thoughtful, fair selection process
What skills do I need?
5 plus years of hands on experience shipping production quality software or data solutions
Strong experience with Python for data processing, and professional experience with Java or Scala is also welcome
Solid knowledge of data related Python packages and common patterns for reliable data processing
Deep understanding of SQL and analytical data warehouses, ideally Postgres
Hands on experience implementing ETL or ELT best practices at scale, including monitoring, testing, and incident handling
Experience with data pipeline orchestration tools, ideally Dagster
Strong data modeling skills, including designing schemas that are clear, performant, and easy to evolve
Confident using Git and modern collaboration practices such as code reviews and pull requests
Ability to ship medium to large features independently, from design to rollout
Strong communication skills, including explaining technical choices to different audiences and building alignment across teams
Skills and experiences that can boost your application
Experience setting up data quality checks and automated tests for pipelines and datasets
Familiarity with lineage, cataloging, or governance style workflows and ways of working
Experience with dlt or similar data ingestion and loading frameworks
Experience building and maintaining on premises infrastructure for data platforms and tooling
Experience developing RESTful APIs and working with service to service integrations
Familiarity with data lake architectures and patterns
What can I expect from IQM?
An opportunity to work with a passionate and diverse team on an important mission
A unique opportunity to make a real impact on the future of quantum
Growth and progress in a creative and open start-up environment
Meet our people and hear more about IQM by visiting our Youtube channel here >>
We'll proceed with the interviews immediately, so please submit your application soon.
Please note that only applications submitted through the website will be processed.
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