We’re on a mission to close the world’s tech skills gap.
We help organisations navigate the future of technology, combining human expertise, emerging tech and AI to deliver better outcomes, faster.
Since 2014, we’ve worked side-by-side with clients to solve complex challenges, build high-performing teams, and create lasting capability. As technology continues to evolve, we believe the most successful organisations will be those that combine the best of both: human ingenuity AND intelligent technology.
That belief is embedded in everything we do. We call it the genius of the AND: deep expertise AND practical delivery, innovation AND responsibility, ambitious work AND sustainable careers.
Through our Guide, Build and Equip approach, we help organisations embrace change, deliver meaningful impact, and develop the skills they need to thrive in an increasingly agentic world.
About you:
- You care deeply about producing high-quality work that delivers real value
- You’re comfortable navigating ambiguity and solving complex problems collaboratively
- You bring strong expertise in your craft, alongside a willingness to keep learning
- You communicate clearly and build trust quickly with clients and teammates
- You’re pragmatic, adaptable and outcome-focused
- You enjoy sharing knowledge and helping others grow
- You value low-ego collaboration and enjoy working as part of multidisciplinary teams
As a Lead Data Solution Engineer, you’ll help our clients deploy and maintain data pipelines in a production-safe manner, using the latest technologies and with a DataOps culture. You’ll work in a fast moving, agile environment, within multi-disciplinary teams, delivering modern data solutions to clients of different sizes and from various sectors.
Your responsibilities:
- Develop pipelines that bring data to life for decision-making, either delivering insight or for more sophisticated AI & machine learning applications
- Experience in being hands on with data, applying the practicalities of quality, flow, and organisation of information, and an understanding of data modelling approaches.
- Be comfortable working in a fast moving, agile environment, within multi-disciplinary teams, delivering modern data platforms for different-size organisations.
- Practical hands-on experience of designing, architecting & deploying AI-enabled solutions at least one cloud data platform (e.g. Databricks, Snowflake, AWS, Azure or GCP) and experience of associated technologies (for example with AWS: DynamoDB, Redshift, Kinesis Pipelines, Glue, Lambda, QuickSight, etc) ideally including practical/hands-on experience of migration to or adoption of a cloud data platform.
- Strong Databricks expertise is a must (ideally with appropriate certifications) with Snowflake and/or MS Fabric experience a bonus.