Paul Smith is one of Britain’s leading independent design companies. We champion positivity, curiosity and creativity. These qualities underpin every Paul Smith design, whether it’s a shirt, a shop or a special collaboration. Reaffirming the values that Paul set down in 1970, ‘classic with a twist’ remains the guiding principle of the company. Happily positioned between high fashion and formalwear, while taking reference from both, Paul Smith has always been proud to stand apart.
The Role
* Design, build, and maintain scalable ETL/ELT pipelines across Azure Data Factory, Synapse, Dataflows Gen2, and Microsoft Fabric.
* Ingest data from diverse sources (REST APIs, SFTP, on‑prem systems, SQL Server, cloud applications, flat files, JSON, CSV, Parquet).
* Implement medallion/lakehouse architecture (Bronze, Silver, Gold) using Delta Lake, Fabric Lakehouse, or Databricks.
* Develop and optimise SQL, Python, and PySpark‑based transformations for efficient data processing.
* Support the build and operation of Azure cloud data services including Azure Data Lake Storage (ADLS Gen2), Azure Synapse Analytics, Azure Functions, Logic Apps, Key Vault, and DevOps CI/CD pipelines.
* Contribute to scalable, secure, and cost‑optimised platform design in collaboration with BI and IT.
* Apply strong data management practices including data validation, DQ monitoring, metadata completeness, and schema enforcement.
* Use tools such as Microsoft Purview, Fabric monitoring, or custom frameworks to maintain governance, lineage, and compliance.
* Ensure data reliability, resilience, and integrity across all datasets and pipelines.
* Build and maintain curated, well‑modelled datasets for analytics and Power BI semantic models.
* Collaborate with analysts to define KPIs, business rules, and data structures that support reporting consistency.
* Provide technical guidance on Power BI data modelling, DAX optimisation, and dataset performance.
* Partner with business stakeholders to understand data needs and translate them into scalable technical solutions.
* Work cross‑functionally with teams across Digital, Retail, eCommerce, Merchandising, Marketing, and Finance.
* Contribute to documentation, knowledge sharing, and mentoring of junior team members when required.
Your Skills & Experience
* Degree in Data Engineering, Computer Science, Analytics, or relevant discipline (or equivalent hands‑on experience).
* Industry certifications beneficial.
* Strong SQL experience (T‑SQL, stored procedures, performance tuning).Experience building ETL/ELT pipelines in Azure Data Factory, Synapse, or Fabric Dataflows.
* Hands‑on experience with Microsoft Fabric (Lakehouse, Data Engineering, Data Pipelines).
* Strong understanding of Azure data services: ADLS, Synapse, Functions, Key Vault.
* Proficiency in Python and/or PySpark for data engineering tasks.
* Experience modelling data structures for reporting and analytics (Kimball, Star Schema, SCD1/2).
* Experience working with Power BI datasets and data modelling.
* Experience with Databricks, Delta Lake and medallion architecture is desirable.
* Familiarity with CI/CD pipelines using Azure DevOps or GitHub.
* Knowledge of data governance frameworks and tools such as Purview.
* Exposure to AI‑driven data engineering patterns (embeddings, LLM‑based retrieval).
* Understanding of cost optimisation and cloud resource management.
What’s In It For You
* A generous seasonal clothing allowance.
* A discretionary discount on Paul Smith products.
* Private health insurance with Vitality.
* Wellbeing support through the Retail trust for you and your family.
* An annual leave entitlement of 25 days, plus Bank Holidays.
* Cycle to work and travel loan schemes.
* SmartTech.
* A day for change.
Find out more about our company culture and the full list of benefits we can offer you.
At Paul Smith, we celebrate and encourage applications from all walks of life into our growing workforce. We are committed to empowering people from any background, belief system, or ethnicity, offering an inclusive environment where talent is recognised and valued.
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