2 of 2 Remote Azure Data Factory Jobs in Slough

Data Services Database and Infrastructure Consultancy Data Engineering & Analytics Adoption and Change Management Their reputation is built on strong consulting skills, deep expertise in Microsoft Data Services, and a highly collaborative culture. They place a premium on client engagement, commercial awareness, and internal collaboration to drive results. Role Overview As a Consultant, you will … insights using tools like Power BI Promote user adoption, training, and change management initiatives Ensure high standards of documentation and data security compliance Technical Skills (desirable): Microsoft Azure Data Services (e.g., Azure Data Factory, Synapse, Databricks, Fabric) Data warehousing and lakehouse design ETL/ELT pipelines … learning Big Data frameworks (e.g., Hadoop, Spark) Data visualisation (e.g., Power BI) Understanding of statistical analysis and predictive modelling Experience: 5+ years working with Microsoft data platforms 5+ years in a customer-facing consulting or professional services role Strong understanding of data warehousing and BI principles Skilled in data modelling More ❯

Job title: Data Engineer Client: Award Winning FinTech Firm Rate: Up to £675 p/d Duration: 6-Month Rolling Contract | Long-Term Engagement Location: London Skills: Python/Azure/Databricks/Snowflake The Role: Design and build powerful data pipelines that fuel real-time decisions, machine learning, and next-gen analytics at … scale. Transform raw data into trusted, usable assets - the foundation for everything from executive dashboards to product innovation. Own the data flow from ingestion to insight - using modern tools like Python, Azure, and Databricks. What you need: 7+ years of hands-on experience in data engineering roles. Advanced skills in Python for … data pipelines, transformation, and orchestration. Deep understanding of the Azure ecosystem (e.g., Data Factory, Blob Storage, Synapse, etc.) Proficiency in Databricks (or strong equivalent experience with Apache Spark ). Proven ability to work within enterprise-level environments with a focus on clean, scalable, and secure data solutions. If you are More ❯