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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

This is not your typical DevOps role. Expect to be hands-on, solving complex infrastructure challenges, and shaping how a modern platform evolves in a hybrid and self-managed ecosystem.

What You'll Be Doing:

-Owning and evolving large-scale Kubernetes clusters in an on-premises environment.
-Driving improvements in platform reliability, scalability, and performance.
-Building automation and backend tooling (primarily in Python).
-Working across Dev, Ops, and Infrastructure in a true platform engineering capacity.
-Contributing to CI/CD pipelines and GitOps workflows.
-Collaborating with cross-functional teams on architecture and platform strategy.

Requirements:

-Deep experience with Kubernetes in self-managed / on-prem environments.
-Strong Linux expertise (this is absolutely key).
-Solid platform engineering / DevOps background.
-Proven ability building automation, tooling, and services in Python.
-Experience with containerisation (Docker) and distributed systems.
-Strong experience with CI/CD and infrastructure as code.
-Familiarity with GitOps approaches (e.g. Argo CD).

Nice to have:

-Exposure to hybrid cloud / AWS environments.
-Experience working in large-scale, high-availability systems.
-Knowledge of backend frameworks (FastAPI, Flask, Django).
-Experience in performance-critical or data-intensive platforms.

Role Overview:
As a Senior Solution Architect, you'll play a key role in shaping and delivering scalable, secure, and high-performing cloud solutions. You'll work closely with engineering teams, stakeholders, and business leaders to define architecture strategy and ensure best practice across AWS environments.

Key Requirements:

-Proven experience as a Senior Solution Architect in enterprise environments.
-Strong expertise across AWS services (e.g. EC2, Lambda, S3, RDS, VPC, etc.).
-Solid DevOps background - CI/CD pipelines, automation, infrastructure as code (e.g. Terraform, CloudFormation).
-Experience designing scalable, resilient cloud architectures.
-Strong understanding of cloud security and governance.
-Ability to work closely with development and operations teams.
-Excellent stakeholder communication skills.
-Swedish Speaking.

Nice to Have:

-Experience with containerisation (Docker/Kubernetes).
-Prior experience in large-scale digital transformation programmes.
-AWS certifications (e.g. Solutions Architect Professional).

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

Key Responsibilities

* Develop and maintain semantic data models and Power BI dashboards
* Ensure data quality, consistency, and well-defined KPI logic
* Translate business requirements into scalable and user-friendly BI solutions
* Work with Power BI (DAX, Power Query/M) and Microsoft Fabric
* Manage data refresh processes, monitoring, and solution stability
* Document data models, logic, and data sources

Additionally, you will contribute to the development of evolving data architecture, including:

* Supporting proof-of-concept initiatives for modern data pipelines
* Working with data ingestion from systems such as Oracle and other operational sources
* Prototyping data transformation and processing using Python
* Contributing to workflow orchestration using tools such as Apache Airflow
* Supporting SQL Server (on-premises) as part of a centralized data layer
* Assisting in the development of dimensional models aligned with business requirements

Technology Environment

Current Core Stack:

* Power BI (data modeling, DAX, Power Query/M)
* SQL
* Microsoft Fabric
* Data sourced from Oracle and other operational systems

Emerging / Proof-of-Concept:

* Python for data processing and prototyping
* Apache Airflow for orchestration
* SQL Server (on-premises)
* Dimensional data modelling

Future Direction:

* Potential transition toward a cloud-based architecture (e.g., Microsoft Azure)
* Increased focus on scalable data engineering and advanced analytics

Qualifications

* Strong proficiency in Power BI (data modelling, DAX, M)
* Solid SQL skills
* Understanding of modern data modelling concepts (e.g., star schema, dimensions)
* Familiarity with Microsoft Fabric or similar platforms
* Ability to translate business needs into technical solutions
* Strong communication and collaboration skills
* Fluency in English and Swedish

Preferred:

* Experience with Python and/or Apache Airflow
* Experience working with Oracle or similar data sources
* Familiarity with ETL/ELT processes
* Experience with version control (e.g., Git)
* Interest in cloud platforms such as Microsoft Azure

Personal Attributes

* Structured and detail-oriented
* Strong analytical and problem-solving skills
* Comfortable working both independently and in cross-functional teams
* Able to communicate effectively with both technical and non-technical stakeholders

Data Scientist

Rate: 1150 SEK per hour

We're currently looking for an experienced Data Scientist to join a growing team and help turn data into meaningful business outcomes.

This is an opportunity for someone who enjoys solving complex problems, uncovering valuable insights, and building machine learning solutions that support strategic decision-making. You'll work closely with both technical and business stakeholders, using data to drive innovation, improve processes, and create measurable impact.

What You'll Be Doing

* Collecting, cleaning, and analysing large structured and unstructured data sets.
* Building predictive models and machine learning solutions to address real business challenges.
* Designing and running statistical analyses, experiments, and hypothesis testing.
* Creating dashboards, reports, and visualisations that communicate insights clearly to both technical and non-technical audiences.
* Working with engineering teams to deploy, monitor, and improve machine learning models in production.
* Identifying opportunities for automation and data-driven optimisation across the business.
* Partnering with stakeholders to understand business requirements and translate them into analytical solutions.
* Maintaining high standards around data quality, governance, and best practices.
* Keeping up to date with the latest developments in AI, machine learning, and data science.

What We're Looking For

* A degree in Data Science, Computer Science, Mathematics, Statistics, Engineering, Physics, or another quantitative field.
* Proven commercial experience as a Data Scientist or in a similar analytical role.
* Strong Python and/or R programming skills.
* Experience working with SQL and large-scale data sets.
* Hands-on experience developing, training, and evaluating machine learning models.
* Solid understanding of statistics, probability, and predictive modelling techniques.
* Experience with tools and frameworks such as Scikit-learn, Pandas, NumPy, TensorFlow, or PyTorch.
* Experience creating visualisations using tools such as Power BI, Tableau, or Matplotlib.
* Excellent communication skills with the ability to explain complex concepts to different audiences.

Nice to Have

* Experience with AWS, Azure, or Google Cloud Platform.
* Knowledge of MLOps, CI/CD, and model deployment pipelines.
* Experience with Spark, Databricks, or other distributed data processing technologies.
* Familiarity with Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG).
* Previous experience working in Agile environments.

The Right Person Will Be

* Naturally curious and analytical.
* A strong problem solver who enjoys tackling complex challenges.
* Self-motivated and highly organised.
* Collaborative and comfortable working across multidisciplinary teams.
* Passionate about using data and AI to create business value.

If you're excited about applying data science, machine learning, and AI to solve real-world problems and want to work in a collaborative, forward-thinking environment, we'd love to hear from you.