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Location
In office (Berlin)
Seniority
Junior · 2+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 16, 2026. First seen by Alion on May 12, 2026. Netlight scores D on the Alion truth index.

Overview
Company
Impact
Profile match
Netlight is a Swedish technology consultancy founded in 1999 and headquartered in Stockholm. It provides software engineering and digital strategy for large clients. The company operates across the Nordics and central Europe.

About the role

As a Data Platform & Data Architecture Consultant, you are the person clients trust to turn their data infrastructure from a bottleneck into a competitive advantage. You design data landscapes, stand up and scale cloud data platforms, and set the guardrails that let entire organisations build on data safely and efficiently.

Our consultants bring varied paths and perspectives to this work. What unites them is structural thinking, a drive to understand the business context behind every technical decision, and the ability to operate across both the blueprint and the build. Across engagements, you may operate as a data architect, lead a platform build, or contribute at the strategic advisory level, often blending several of these roles within a single engagement.

What the work looks like

Building and operating platforms. You design, provision, and harden cloud data platforms end to end, covering storage and compute, networking, security and IAM, observability, and cost. You codify infrastructure using tools like Terraform, Pulumi, or CloudFormation and establish governance frameworks such as data catalogs, data contracts, RBAC models, and SLAs that let organisations scale data access without losing control. You build platforms that multiple teams and business domains can rely on, not just at launch, but as they grow.

Shaping the data architecture. You design logical and physical data models, map data flows and lineage across systems, and make the structural decisions that determine how data is organised, integrated, and consumed. This can mean designing a target-state architecture for a client migrating from legacy systems to a modern cloud lakehouse, or defining domain boundaries and data product interfaces in a data mesh adoption.

Advising and translating. You sit at the intersection of technology and business. You work with data engineers, data scientists, product owners, and senior client stakeholders to understand what they need, then turn that into platform strategy and architecture decisions. You are the person a CTO trusts to make the right call on how their data infrastructure should evolve.

Minimum Qualifications

    • Master’s Degree in Engineering or Technology (e.g., Computer Science, Data Engineering, Information Systems, or similar)
    • Verbal and written fluency in English
    • 2-4 years of full-time work experience in cloud data infrastructure, data platform engineering, or data architecture. Experience working in agile product or delivery teams, gained after completing your Master's degree
    • Strong hands-on experience with at least one major cloud platform (AWS, Azure, or GCP), including compute, storage, networking, and identity management
    • Practical experience with at least one modern cloud data platform such as Snowflake, BigQuery, Databricks, Redshift, or Microsoft Fabric
    • Experience with Infrastructure as Code (e.g., Terraform, Pulumi, or CloudFormation) and modern CI/CD and DevOps workflows
    • Experience with data modeling, data architecture, or designing data flows and integration patterns across systems
    • Experience designing or operating data governance, security controls, and platform observability in environments serving multiple teams or domains
    • Demonstrated ability to collaborate with diverse stakeholders including engineers, analysts, product owners, and business leaders in client-facing settings

Preferred Qualifications

    • Experience with data mesh, data product, or data lakehouse architectures at an organisational level
    • Depth in enterprise data architecture, including conceptual, logical, and physical modeling, data lineage, and approaches such as dimensional modeling or Data Vault
    • Hands-on experience with multi-tenant platform design or multi-cloud environments
    • Familiarity with container orchestration (Kubernetes, Docker) in data platform contexts
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