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Overview

We're working with a client looking for a strong Azure Data Architect / Engineer to help shape and build out their data platform.

It's a mix of hands-on engineering and higher-level design, with a big focus on modern tooling across Azure and Microsoft Fabric. They're moving towards a more unified, lakehouse-style setup, so it's a good opportunity to work on something fairly greenfield rather than just maintaining legacy pipelines.



What you'll be doing

* Designing and building data pipelines across Azure and Fabric
* Working on lakehouse architecture (Fabric / Data Lake)
* Getting involved in data modelling for reporting and analytics
* Helping move existing solutions into a more modern Azure/Fabric setup
* Working closely with analysts and business stakeholders to understand requirements
* Keeping an eye on performance, cost, and general optimisation
* Inputting into architecture decisions (especially if you're more senior)



What they're looking for

* Solid experience across Azure data services (ADF, Synapse, Data Lake, Azure SQL)
* Some exposure to or interest in Microsoft Fabric (OneLake, pipelines, warehouse, etc.)
* Strong SQL and data modelling fundamentals
* Experience building ETL/ELT pipelines end-to-end
* Python and/or Spark (Databricks or Fabric) is a big plus
* Comfortable working in a fairly collaborative, non-siloed environment



If interested, please reach out.

Location: Stockholm
Contract: Freelance
Onsite: 2-3 days per week
Duration: Until end of 2026



What You'll be Doing:

-Designing, developing, and maintaining tools that orchestrate and manage thousands of range systems at scale.
-Ensuring servers can be effortlessly provisioned, configured, and managed through robust internal tooling.
-Building and evolving monitoring and observability solutions that provide real-time insights across all running software.
-Supporting internal teams through reliable release management and regression testing environments.
-Working hands‑on with hardware‑adjacent systems-servers, screens, cameras-within Linux-based ecosystems.

Requirements:

-Senior-level background in software engineering
-Expert-level Kubernetes knowledge
-Strong Python development skills
-Solid experience with Linux environments
-Someone who enjoys owning technical decisions, improving system scalability, and delivering clean, reliable code

Azure Data Platform Engineer - Contract - Fully Remote

We're looking for highly capable Azure Platform Engineers to support a large‑scale cloud and data engineering programme. This environment is fast‑paced, technically mature, and heavily invested in modern Azure, IaC, and Databricks ecosystems. Strong technical depth and clear, concise communication are essential. Outisde IR35
Remote
6 months contract

Core Technical Requirements
Azure Platform Engineering

Deep hands‑on experience building and operating cloud‑native platforms in Azure
Strong understanding of Azure networking, identity, security baselining, and landing zone patterns
Experience working in highly automated, scalable, enterprise-grade environments

Terraform (IaC)

Solid production experience delivering infrastructure via Terraform
Strong module design, state management, secret handling, and CI/CD integration
Ability to define, manage, and version cloud resources using best‑practice IaC patterns

Databricks

Practical experience supporting, deploying, or engineering Databricks workspaces
Strong knowledge of cluster configuration, job orchestration, workspace governance, and optimisation
Comfortable working alongside data engineers and platform squads

Unity Catalog (Highly Advantageous)

Experience implementing or working within Unity Catalog for centralised governance
Understanding of cataloguing, lineage, secure data access, and workspace-level controls
Ability to support migration from legacy Hive Metastore to Unity Catalog is a major plus

Soft Skills & Delivery

Clear, concise communicator (no overly long CVs - brevity and clarity matter)
Strong problem‑solver who can operate independently in a remote environment
Able to articulate platform decisions and engineering rationale effectively
Comfortable working in cross-functional teams following modern DevOps practices

Please can you send me a copy of your CV if you are interested.

The Role

We are hiring a Senior Data Platform Engineer to help build and scale a cloud-based data platform in a highly regulated environment.

The organisation is partway through its migration to Azure, with production workloads already in place. The focus now is not strategy or architecture it's execution: building reliable, production-grade data platforms that will underpin future data and AI capabilities.

This role is for engineers who have actually built platforms within azure databricks, not just contributed to them or designed them at a high level.

You will be working in a low-risk environment, where data security, governance, and cost control are critical. The expectation is that you can deliver within those constraints, not work around them.

Responsibilities

* Building and operating Azure Databricks-based data platforms used in production
* Developing end-to-end data pipelines using Python and SQL
* Configuring and optimising Databricks environments, including:

* Cluster setup, tuning, and troubleshooting
* Job orchestration and scheduling
* Managing performance vs cost trade-offs

* Implementing data transformation and modelling workflows (dbt or similar)
* Owning platform components from initial build through to production support
* Ensuring data platforms meet strict security, governance, and risk requirements
* Contributing to ongoing cloud migration and platform modernisation work

Required Experience

* Strong, hands-on experience building Azure Databricks data platforms from scratch
* Proven track record delivering and supporting production-grade data pipelines
* Solid experience with:

* Azure
* Azure Databricks
* Python
* SQL

* Experience working with data at scale (not just small or isolated datasets)
* Background in regulated or enterprise environments with governance constraints
* Comfortable working in cost-sensitive environments where efficiency matters

Nice to Have

* Hands-on experience with dbt in production
* Experience in financial services or similar regulated industries
* Exposure to cloud migration programmes
* Experience optimising Databricks for performance and cost

Why This Role

* Opportunity to build real, production data platforms, not just prototypes
* Direct impact on a platform that will enable future AI and data capabilities
* Work in an environment where engineering quality, security, and reliability actually matter
* Join a team that values delivery over theory