On AWS, you're fluent across the core services, for example:

On Azure, you’re fluent across the core services, for example:

• Data Product mentality: You build Data Products where every pipeline and dataset is discoverable, addressable and secure by design.
• Data capabilities: You know the full data lifecycle, from discovery, storage, pipelines, ETL and streaming to data quality, governance, metadata management and cataloguing, through to advanced analytics and decision-making.
• AI: You understand how AI is built and deployed in modern data platforms (Databricks, Snowflake) and cloud-native services like Amazon Bedrock, with enough depth to guide teams and advise clients, spanning LLMs and SLMs, agentic automation, Human in the Loop and MLOps.
• Data Architecture Design: You know when to use RAG (Retrieval-Augmented Generation), Serverless, DWH models, Data Mesh, Data Fabric, Medallion and Data Products.
• Hands on mindset: Fluent in the language of data, whether SQL, Python, PySpark, R or Scala. Open formats including Parquet, Iceberg and JSON.

Agile Ways of Working

• Run and contribute to agile ceremonies, helping to shape and improve the agile process
• Work with the project’s delivery manager and product owner to lead the team in delivering high quality digital products
• Lead and support your peers in technical conversations
• Be an advocate for lean development, building for what is required now
• Pairing with other members of the team, including designers

Consulting with Clients

• Own the relationship with the client’s technical stakeholders
• Proactively engage with clients to shape and move the project forward, including giving updates on the delivery progress and highlighting potential technical blockers
• Upskilling and embedding modern data practices in client teams where necessary

Leadership & Influence

• Data Leadership: A proven track record of managing and inspiring teams, navigating enterprise-scale problems and turning them into opportunities for clients.
• People-first leadership: You guide, mentor and grow your team, bring the Red Badger culture with you, and build effective, high-trust teams where everyone is heard and valued.
• Stakeholder Artistry: You are a master of client-facing delivery. You can translate complex data concepts into business value, managing multi-vendor environments with a focus on long-term partnership. Lanyards off, you embed as one team rather than an outside supplier.
• Designing for People and Purpose: Your expertise goes beyond just building scalable architectures; you design systems with a focus on delivering value. You ensure that your extensible and scalable solutions are implemented because they consistently meet the evolving needs of both the business and its users.

Your experience

It’d be great if you

• Quality Advocate: You take pride in the integrity of your work, championing quality assurance and performance tuning so the data solutions we build are robust, reliable and respected.
• Industry Stewardship: A lifelong learner who keeps a pulse on industry standards and best practice.
• Partnership Focus: You build strong relationships with technology partners, established or new, to deliver the best outcomes for clients.

You care deeply about high-quality work that delivers real value

• You're comfortable with 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 fast with clients, data engineering leaders and data and software engineers
• You're pragmatic, adaptable, outcome-focused and low-ego in multidisciplinary teams
• You lead with a people-first attitude, helping others grow and making sure people are heard, valued and set up to thrive

It’d be amazing if you can also

• Negotiate SLAs and SLOs with the business and supporting teams
• Help shaping and resourcing technical teams
• Articulate commercial objectives into a technical strategy
• Show a track record of owning the tech leadership on complex data projects, setting the technical vision for the project and managing technical stakeholders
• Coach and line manage data engineers and data delivery individuals who are starting their line management journey
• Be a part of the public face of the company in media and at meetups, conferences, etc.