Data Engineer / Senior Data Engineer with Azure, Databricks and Microsoft Fabric

DataArt
London, UK
15 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
6 years minimum
Working hours
Regular working hours
Languages
English
Job source

Tech stack

Artificial Intelligence Computing Platforms Microsoft Azure Business Systems Code Review Computer Programming Information Engineering Data Systems Data Vault Modeling Dimensional Modeling Python (Programming Language) Meta-Data Management
+19 more
Microsoft SQL Server Power BI Azure Data Lake SQL Databases Cloud Platform System Azure Data Factory GitHub Copilot Apache Spark Git Microsoft Fabric Data Lakes Pyspark Data Lineage Star Schema Data Pipelines Server Operating Systems & Platforms Service Stack Legacy Systems Databricks

Job description

Position overview: We are looking for a Senior Data Engineer with strong experience in Azure, Databricks, and Microsoft Fabric to help design and build a modern cloud data platform. You will contribute to the ingestion, transformation, and curation layers of the platform while collaborating with technical and business stakeholders. In this role, you will also support engineering standards, platform design decisions, and the delivery of scalable data solutions. Technology stack: Azure Data Factory, Azure Databricks, Microsoft Fabric, Azure Data Lake Storage Gen2, Delta Lake, Apache Spark, PySpark, Python, SQL Server, Azure DevOps, Git, Power BI, Microsoft Purview, GitHub Copilot

  • Responsibilities: Design and develop data ingestion pipelines from business systems into a governed cloud data platform.
  • Build scalable data engineering solutions using Azure Databricks and Microsoft Fabric.
  • Implement medallion architecture patterns and reusable engineering frameworks.
  • Develop curated data products and analytical datasets for business reporting and decision making.
  • Apply AI assisted development practices while ensuring quality, governance, and auditability.
  • Contribute to data modelling, semantic models, metadata management, and analytical solutions.
  • Support the migration of reporting and analytics workloads from legacy platforms.
  • Collaborate with stakeholders to translate business requirements into technical solutions.
  • Provide design guidance, establish engineering standards, and participate in code reviews.

Requirements

  • 6+ years of experience in Data Engineering.
  • Hands on experience with Azure Data Factory, Azure Databricks, and Azure Data Lake Storage Gen2.
  • Strong programming experience with Python, SQL, and PySpark.
  • Experience implementing Delta Lake and production lakehouse or medallion architectures.
  • Experience with Git and Azure DevOps, including CI/CD pipelines for data solutions.
  • Experience working with SQL Server environments.
  • Practical experience using AI coding assistants within software delivery projects.
  • Ability to communicate effectively in English with technical and business stakeholders.
  • Experience taking ownership of architecture or platform design decisions.
  • Experience reviewing code and establishing engineering standards.
  • Experience gathering requirements and collaborating directly with business stakeholders.

  • Nice to have: Experience implementing Microsoft Fabric in production environments.
  • Microsoft certifications including DP 203, DP 600, DP 700, AZ 900, or DP 900.
  • Databricks Data Engineer Associate or Databricks Data Engineer Professional certification.
  • Experience with dimensional modelling, including star schema, snowflake schema, or Data Vault.
  • Experience with semantic modelling in Power BI or Microsoft Fabric.
  • Knowledge of Microsoft Purview, data lineage, and metadata management.
  • Experience working in regulated financial services environments.

About the company

Client: Our client is a UK financial services group operating in a highly regulated environment.

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