Data Engineers (several seniority levels)

KONE Technology and Innovation (KTI) is where the magic happens at KONE. It's where we combine the physical world – escalators and elevators – with smart and connected digital systems. We are changing and improving the way billions of people move within buildings every day. We are on a mission to shape the future of the industry with new technologies and sustainable innovations.

We are looking for a

Data Engineers, Senior Data Engineer and Lead Data Engineer (Databricks on AWS)

To join the team developing and operating our Data Foundation data domains in our Espoo office in Finland.

We are searching for Data Engineers of several seniority levels - Data Engineers, Senior Data Engineer and Lead Data Engineer. Our Data Foundation is a cloud based distributed data platform built upon data mesh approach. Data Foundation is key enabler in our digital transformation creating ability to develop new scalable analytics, AI and digital use cases by leveraging data across the whole KONE organization. Data products play a vital role in business value generation and driving optimized data architecture is crucial to ensure reusability of the data assets on the Data Foundation.

In our Data Engineer roles, you will be doing various data engineering tasks in the respective data domain for developing and operating data products. The work will encompass the full data engineering lifecycle: new development, resolving technical issues, maintaining, optimizing workloads and continuous improvement. All our Data Engineer roles are hands-on, roll up your sleeves positions that require a passion for data, engineering and DevOps.

We offer a chance to work hands-on with state-of-the-art cloud technology, lake house architecture based on Databricks and Delta Lake on AWS, relying on the multi-hop medallion architecture to divide the data lake into bronze, silver and gold layers based on the quality and reusability of the data stored there, and relying on Unity Catalog for publishing data products. An ideal candidate has a strong background in either data engineering, SW engineering, or data science, but above all the desire to commit to a DevOps mindset, reaching goals together and continuously striving to improve the team performance.

We are searching for enthusiastic persons to join the team who are excited about developing own professional skills even further, learning new things and contributing to team success. We are expecting you to take self-driven, proactive approach to your work, find & implement solutions, solve problems, and share the learnings to colleagues. We want to work with people who enjoy teamwork, are not afraid to step out of their comfort zone, want to help others and share information.

All the positions are based in Espoo, Finland.

To succeed best in Data Engineer roles, the following professional experience will play a key role:

• Master's or Ph.D. degree in either software engineering, data engineering, data science, computer science, physics, statistics, mathematics, or a related field.
• 3-10 years of hands-on data engineering professional experience depending on the seniority of the role
  • Technical proficiency with our cloud stack: AWS, Gitlab/GitHub, Databricks, Airflow, Python, SQL, PySpark, and DBT for developing and orchestrating ETL jobs, AWS CDK and Terraform for IaaC.
  • Previous hands-on professional experience in developing and maintaining data pipelines on Databricks and AWS. Relevant AWS and Databricks certificates preferred.
  • Ability to write compelling code, technical documentation and visualize your technical design. Coding proficiency with Python and SQL (experience with Scala and DBT is considered a plus) with proven hands-on experience in industry standard software development life cycle methods, experience with software testing practices and DevOps practices spanning the full solution lifecycle.
  • Good understanding cybersecurity guidelines, data privacy and compliancy regulations.
  • Practical experience in working with enterprise data landscapes and data structures: Structural data, non-structural data, metadata, master data, transactional data, batch/NRT. Experience on enterprise data sources such as e.g. SAP ERP, Salesforce and product data management (PDM).
• For Senior and Lead Data Engineer positions you are expected also to have proficiency in:
  • Acting as the go-to person in the methodological and technical aspects of data engineering, promoting innovation in data engineering, critically evaluate new data engineering methods and applying them to practice.
  • Identifying, designing, and implementing data engineering process improvements, e.g. automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability.
  • Ensuring pipelines are implemented wi