Data Engineer - Range Experience

at  IKEA

Job ID: R0006201
Date posted: 04/11/2024
Company description
The goal of Range Experience - IKEA Planning experience is to support and empower customers to find their personal best home furnishing solutions. We run and develop digital solutions used by customers and co-workers enabling them to design homes and home furnishing solutions for the entire IKEA range for all IKEA retailers. Part of our portfolio are planning solutions for Kitchens, Bathrooms, Storage solutions, Beds… Our next big step ahead will be to enable customers to design their full homes.
Our customers should experience an inspiring, fun, simple and rewarding planning journey based on their needs and preferences. Our co-workers and service partners should experience a fun, efficient and unbroken sales process.
The solutions and capabilities we develop are an integral part of the entire seamless buying and selling experience and a key contributor to converting visitors into happy customers and to engaging with our customers from the start. Utilising data around and about our products to create more personalised experiences is an integral part of the work we do.
Range Experience deliver solutions to all IKEA retailers spanning over 50 markets worldwide and over 400 stores and IKEAs digital channels. All solutions are made to help customers and co-workers in all customer meetings, from a mobile phone to the largest IKEA store in the world.

BEING A DATA ENGINEER IN THE RANGE EXPERIENCE TEAM

As a Data Engineer in the Range Experience team, you will be responsible to design, build and maintain the data pipelines and tools that enable our teams to work in a data driven way. You will work very close to other Data engineers, Data scientists, Product teams and other stakeholders. You will be part of creating solutions that enable customers to design any space in their homes and businesses and configure home furnishing solutions digitally. Exploring and utilising different technologies and approaches to achieve the best result is a natural part of everything you do. With your data driven mindset you are a strong ambassador and driver for the data literacy and culture in Range Experience.
Job description

REQUIRED/RELEVANT WORK EXPERIENCE:

• Strong knowledge in designing efficient, robust and automated data pipelines, ETL workflows, data warehousing and Big Data processing.
• Hands-on experience with database design in varying concepts.
• Working experience with Python or PySpark is required.
• Working experience and understanding of Azure Databricks, Azure Data Factory, Azure Data Lake, Azure SQL DW, and Azure SQL is required.
• Experience in business processing mapping of data and analytics solutions.
• The ability to apply such methods to solve business problems using one or more Azure Data and Analytics services in combination with building data pipelines, data streams, and system integration.
• Experience in driving new data engineering developments (e.g. apply new cutting-edge data engineering methods to improve performance of data integration, use new tools to improve data quality, etc.)
• Experience preparing data for Data Science and Machine Learning.
• Preferred experience in retail and/or market research.
  You enjoy an Agile and iterative, yet structured way of working and achieving results together with a team in a flexible environment, but also have a strong individual drive to deliver high quality results on time. You have great communication and networking skills and are fluent in written and spoken English.
  Qualification

QUALIFICATIONS:

• Bachelor’s degree within Engineering, Computer science, Information Systems, Mathematics or related fields. Master’s degree is preferred within Engineering, Computer science, Information Systems, Mathematics or related fields.
• 5+ years of experience in a similar role or Analyst working in running business activities as well as in agile project environments.
• Experience of working alongside multiple teams and with an understanding of multiple product environments.
  More Information

TO BE SUCCESSFUL IN THIS ROLE

You are passionate about generating continuous value through providing, analysing and utilising data and together with other Data engineers, Data scientist, product team(s) and other stakeholders. You thrive in understanding data needs and assisting in development of models and analysis.
You have an interest and proven track record in finding the most efficient ways to extract, transform and load data from different sources, to ensure that our digital solutions fulfil and adapt to actual and future business needs. Staying up to date with the latest technologies and best practices in data engineering and bringing this specialised knowledge to the whole organisation is a part of your toolbox. You have a great interest in the world around you and keep yourself updated with the latest trends and future technology, just as we do.
You make mistakes sometimes that keep you evolving and learning as you are not afraid to find new ways to solve a challenging task together with your colleagues.

YOUR MAIN RESPONSIBILITIES AS THE DATA ENGINEER WILL BE:

• Driving all aspects of collecting, analysing, integrating, modelling, processing and refining data from different sources across the IKEA ecosystem and external sources as needed by your product team or area.
• You will help design, build and maintain data pipelines.
• Evaluate business needs and objectives in collaboration with the Product Team and other stakeholders.
• Explore ways to enhance data quality and reliability.
• Identify opportunities for data acquisition.
• Contribute to the development of analytical tools and programs, ensuring easy and standardised access and sharing of data.
• Work closely together with partners, peers and other relevant roles like data scientists, analysts or architects across IKEA as well as in your team.
• Mentor and coach junior data engineers in the team.
• Ensure application and consistency with relevant digital frameworks, principles, guidelines and standards.
• Document and make the relevant know-how available.