Data Engineer

Data Engineer | Consultant London or Manchester | Hybrid About Us Slalom is a purpose-led, global business and technology consulting company. From strategy to implementation, our approach is fiercely human. In eight countries and 53 markets, we deeply understand our customers (and their customers) to deliver practical, end-to-end solutions that drive meaningful impact. Backed by close partnerships with over 700 leading technology providers, our 10,000+ strong team helps people and organisations dream bigger, move faster, and build better tomorrows for all. We’re honoured to be consistently recognised as a great place to work, named one of the Fortune 100 Best Companies to Work For® from 2016 to 2024, and featured on Glassdoor’s Best Places to Work list from 2016 to 2023. We’ve also been recognised across the UK and Europe for wellbeing, inclusion, and consulting excellence. Since opening our doors in London in 2014, and then the launch of our Manchester office in 2019, it’s been an unforgettable journey. What’s more, we’re at an exciting stage of our growth in the UK and now Ireland, with our Dublin office now well established and growing rapidly. We’re looking for great people who want to be part of that adventure. Our employees are at the heart of delivering impactful and meaningful work for our clients and helping them to reach for and realise their vision. Slalom’s Data & AI Capability At Slalom, we believe that through our trusted relationships with our clients, we can create modern, AI-native data solutions that drive results and improve the world. We are building the data foundations that power agentic AI, production machine learning, and intelligent decision-making at enterprise scale. We expect our engineers to use AI tooling natively in how they design, build, and ship. Interested in strategy? Have a passion for architecture? Want to work in a team that is pushing the forefront of AI, agentic workflows, and modern data engineering? We can offer you this. We work across the leading data and AI ecosystems, including Snowflake (with Cortex and Cortex Code), Databricks, AWS, Azure, Microsoft Fabric, OpenAI, and Anthropic. We’re interested in people who are genuinely curious about what’s next. Data Engineer As a Data Engineer (Consultant) at Slalom, you will design and deliver high-quality data solutions that power AI and generate measurable business value for our clients. You will build the pipelines, platforms, and feature stores that feed modern AI and analytics workloads, using AI tooling as a first-class part of your workflow. You bring solid hands-on experience with Snowflake and Python, a working knowledge of at least one major cloud provider (AWS or Azure), and a genuine interest in the intersection of data engineering and AI. You collaborate effectively within teams, translate client needs into technical solutions, and contribute to the continued growth of Slalom’s Data & AI capability. What you’ll do Client delivery & technical execution Build AI-ready data platforms. Design and implement the Snowflake data layers, feature stores, and pipelines that feed production AI, machine learning, and agentic workloads. Deliver on Snowflake end-to-end. Ingestion, transformation, performance tuning, security, and role design, including native integration with Snowflake Cortex for in-platform AI, LLM, and embedding workloads. Engineer in Python as a core craft. Use Python for data processing, orchestration, automation, and integration with AI/ML services and agentic frameworks, not just as a SQL alternative. Work across the cloud. Implement data architectures on AWS (S3, Glue, Lambda, Redshift) or Azure (Data Lake, Data Factory, Functions, Synapse), with Databricks and Microsoft Fabric experience a strong plus. Use AI natively in how you build. Apply AI-assisted development (code generation, test creation, documentation, pipeline design) as the default way of working. The outcome is measurably faster delivery at higher quality. Partner across disciplines. Collaborate with AI/ML engineers, data scientists, and DevOps teams on integrated solutions: feature pipelines, model-scoring workflows, retrieval layers for LLM applications, and analytics-ready datasets. Apply platform best practice. Security, performance, cost optimisation, and operational excellence across Snowflake and cloud environments. Translate business into technical. Work with architects, analysts, and business stakeholders to turn requirements into implementations. Contribute to consulting delivery. Planning, estimation, and delivery as part of a project team. Client collaboration & communication Participate in client workshops, requirements-gathering sessions, and solution design discussions. Communicate technical concepts clearly to both technical and non-technical audiences, including how AI capabilities shape data design choices. Build positive working relationships with client stakeholders through re