Are you a highly skilled Data Engineer with deep SAP expertise and a passion for cloud-native engineering? Do you thrive in complex, large-scale data environments where your work directly accelerates business impact? Then Multiply Teknik & IT is the place for you.
At Multiply, we combine high-end engineering consulting with our own product ecosystem — VisFlow, VisFlow Embedded™, and Multiply Academy — to deliver end-to-end data, engineering, and lifecycle intelligence for some of Sweden's most advanced industries.
Now we're looking for a Senior Data Engineer who can strengthen our capabilities in SAP and Google Cloud Platform, enabling our customers to build scalable analytical solutions and multiply value with data.
⭐ About the Role
As a Senior Data Engineer at Multiply, you take end-to-end responsibility for building, optimizing, and supporting modern data products across GCP and SAP Datasphere. You will work at the intersection of:
cloud-native data engineering
SAP domain knowledge
Advanced Analytics & Data Modelling
scalable architecture and DevOps practices
collaborative, product-driven development
You support data mesh principles, guide product teams, and serve as a technical leader who drives quality, structure, and innovation across the entire data lifecycle.
This is a role for someone who wants to shape high-impact data solutions that power decision-making, operations, and customer experience.
What You Will Do
Build, enhance, and optimize data pipelines and products on Google Cloud Platform
Manage CI/CD, Terraform, Git, and cloud infrastructure in GCP
Deploy and maintain analytical capabilities in SAP Datasphere
Integrate SAP sources such as ECC, CAR, EWM, POS, Inventory, and General Ledger into GCP-native solutions
Model and provision data using CDS Views, Datasphere modeling layers, and best-practice SAP patterns
Apply strong engineering principles to ensure scalability, security, observability, governance, and performance
Collaborate with Product Owners and cross-domain teams to support data mesh and customer-centric development
Drive continuous improvement, reduce technical debt, and elevate engineering practices
Coach engineers, lead pair programming, and present solutions to complex engineering challenges
Promote Agile ways of working and help teams deliver with speed and quality
Required Qualifications
8+ years of experience in data engineering
Strong expertise with GCP stack: BigQuery, Dataflow, DBT
Deep experience with SAP Retail scenarios (ECC, CAR, EWM)
Advanced understanding of SAP data structures and SAP Datasphere
Hands-on experience with Power BI or other BI tools
Solid knowledge of data formats (Avro, Parquet) and SQL
Programming skills in Python, Java, or Scala
Experience with RDBMS and NoSQL databases
Strong ability to design scalable, enterprise-grade data products
Experience with Integrated Planning/BPC
Excellent communication and collaboration skills
Fluent in English (Swedish is a plus)
Preferred Qualifications
Experience from the retail industry
Familiarity with SAFe or other Agile frameworks
Experience as Scrum Master or in leading Agile ceremonies
Proven ability to solve complex challenges through coding and analytical thinking
Why Multiply?
At Multiply, you join a company that blends:
Knowledge-based consulting
VisFlow – our product ecosystem for engineering intelligence
VisFlow Embedded™ – data generation at the edge
Multiply Academy – structured growth & certification
We deliver end-to-end value: from sensors and embedded systems → to cloud analytics → to modelling, traceability, simulation and decision intelligence.
Our culture is built on Swedish values: trust, humility, transparency, and collaboration. We grow people through continuous learning, strong leadership, and meaningful assignments.
Here, you don't just work on data —
you elevate industries with it.
Join Us
If you're ready to build data solutions that scale, lead cloud-native engineering practices, and shape the future of SAP analytics — then you're ready to become a Multiplier.
Apply now, become a multiplier and help multiply value with data.