Data Engineer (Consultant)
London or Manchester, Hybrid
Slalom is a purpose‑led, global business and technology consulting company that builds end‑to‑end solutions to drive meaningful impact for our clients. In this role, you will design and deliver high‑quality data solutions that power AI and generate measurable business value. You will build pipelines, platforms, and feature stores that feed modern AI and analytics workloads, using AI tooling as a first‑class part of your workflow.
Responsibilities
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 end‑to‑end Snowflake solutions covering 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.
* Work across the cloud. Implement data architectures on AWS (S3, Glue, Lambda, Redshift) or Azure (Data Lake, Data Factory, Functions, Synapse), leveraging Databricks and Microsoft Fabric when appropriate.
* Use AI natively in design. Apply AI‑assisted development (code generation, test creation, documentation, pipeline design) as the default way of working to increase delivery speed and quality.
* Partner across disciplines. Collaborate with AI/ML engineers, data scientists, and DevOps teams on integrated solutions such as feature pipelines, model‑scoring workflows, retrieval layers for LLM applications, and analytics‑ready datasets.
* Apply platform best practices. Enforce security, performance, cost optimisation, and operational excellence across Snowflake and cloud environments.
* Translate business requirements into technical solutions. Work with architects, analysts, and business stakeholders to turn requirements into implementations.
* Contribute to consulting delivery. Participate in 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 reliable delivery and transparent communication.
Practice development & knowledge sharing
* Stay current with the Snowflake, Python, and AI engineering ecosystems, including Cortex, agentic frameworks, retrieval‑augmented generation, and AI‑native data patterns.
* Contribute to internal accelerators, templates, and reusable components for AI‑enabled data engineering.
* Share knowledge through documentation, demos, and informal mentoring of peers, including how you’re using AI tooling to work better.
* Participate actively in Slalom’s learning culture and help shape our approach to agentic data workflows and AI‑driven automation across the data lifecycle.
What you’ll bring
Core experience
* 3 to 5 years of experience in data engineering, with hands‑on work on cloud data platforms.
* Strong practical experience with Snowflake: data modelling, ingestion, transformations, performance tuning, security, and roles.
* Working knowledge of Snowflake Cortex (or strong curiosity and appetite to build it) for in‑platform AI, LLM, and vector workloads.
* Strong proficiency in Python and SQL for data processing, transformation, and orchestration.
* Experience with AWS or Azure data services (e.g. S3/Glue/Lambda/Redshift/Athena/EMR or Data Lake/ADF/Functions/Synapse).
* Experience designing and implementing ETL/ELT pipelines, data integration patterns, and workflow orchestration (e.g. Airflow, dbt, Step Functions, Azure Data Factory).
* Solid understanding of data modelling concepts (dimensional modelling, Data Vault, normalised schemas) and when to apply them.
AI‑native mindset (core, not a nice‑to‑have)
* Active user of AI‑assisted development tools (e.g. Snowflake Cortex Code, Claude Code, GitHub Copilot) as part of your day‑to‑day engineering workflow.
* Curiosity about, and ideally some hands‑on exposure to, agentic AI, retrieval‑augmented generation, or production ML pipelines.
* An understanding of how data engineering decisions shape what AI and ML teams can deliver, and an interest in designing for that context.
Good to have
* Experience with Databricks (on AWS or Azure): notebooks, Delta Lake, and collaborative development.
* Exposure to Microsoft Fabric.
* Awareness of data governance, data quality, and metadata management principles.
* Familiarity with CI/CD and Infrastructure as Code tools (CloudFormation, Terraform, ARM/Bicep, or similar).
* Relevant cloud certifications (AWS, Azure, or Snowflake).
How you work
* Strong problem‑solving skills and the ability to work in fast‑paced consulting environments.
* Solid communication and interpersonal skills, with the ability to collaborate effectively in diverse teams.
* Prior client‑facing experience is preferred but not required. A strong interest in consulting and working directly with clients is important.
Slalom provides equal employment opportunities and does not discriminate based on race, color, religion, sex, national origin, disability, or other protected characteristics.
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