Datasparq are the best boutique data consultancy around

• Architecture, design, development and delivery of enterprise grade data solutions within Microsoft Azure
• Work on high profile projects with well-known clients across various sectors
• Help clients realise the potential of data science, machine learning, and scaled data processing within Azure ecosystem
• Mentor junior team members and support their personal development
• Take ownership for the delivery of core solution components
• Constantly develop technical skills using the latest cloud technology - achieving & maintaining relevant certifications
• Work directly with clients to understand requirements and present solutions to customer sponsors
• Influence and support project delivery through involvement in project/sprint planning and QA.

• Strong communication skills
• Strong background of enterprise data platform development, concepts and methods with the ability to adapt and tailor based on requirements
• Deep understanding of software engineering tools and concepts

This is a role for ambitious technologists who wish to work with the latest cloud technology from Azure, GCP and AWS. Whilst we don’t expect everyone to have experience with all the technologies below, candidates will need to show their ability to rapidly learn new technologies.

• Azure Synapse Analytics/or Azure Databricks
• Synapse DW
• Expert Python and SQL skills
• Expert Version Control skills and workflows (especially Gitflow)
• Good Docker and Kubernetes skills (GKE, EKS, AKS)
• Expert Knowledge of orchestration and data movement tools like DataFactory or Apache Airflow or Luigi
• Good understanding of security concepts
• Linux bash scripting
• IoT and Event Streaming
• Good knowledge of Terraform

• Kubeflow
• Cloud AI tools like Azure ML
• Azure Functions or Lambda Functions
• Microservices Architecture
• Experience with other MPP databases like Snowflake
• Exposure to other public clouds like GCP, AWS
• Consultancy experience

Datasparq is a boutique AI & data firm that solves complex business challenges.

We build bespoke AI and data science tools—and turn them into robust, reliable services for our clients.

We start with research and iterate—using lean startup principles—to quickly uncover impactful solutions to high-value challenges. Our product team ensure that we build the right solution in the right way. Our data science team ensure that the AI and data science solutions we build are best-in-class. And, our engineering team ensure that solutions are robust and ready to be deployed in the real world.

But—what’s special about Datasparq is the way our teams work together.

Just as no business challenge fits neatly into a box, neither do our people. Rather than simply hiring a data scientist or a data engineer, we seek out passionate experts who can bring a range of overlapping skills to any team. That gives us the ability to build the perfect team to solve any challenge. We believe in bespoke over one-size-fits-all.

We don’t just build ML models—we take our science from the broad spectrum of mathematics, statistics, operations research and computer science. We work with academic partners and Centres for Doctoral Training (CDTs) across the UK to ensure that what we do is founded on high-quality, up-to-date science.

When it comes to operationalising solutions, we can run data science products in the cloud as services for our clients—or deploy to their infrastructure as needed.

Diversity & ethics

As a company, we don’t just value diversity—we place it at the heart of what we do. To create solutions that serve our users—and our clients' users—diversity is a must, not a nice to have. Likewise, we place ethics at the heart of what we do. Our team are passionate about working on projects that drive positive results for people and the planet. We routinely undertake ethics reviews and champion a culture of openness, honesty and integrity.