Engineer the Quantum RevolutionYour expertise can help us shape the future of quantum computing at Oxford Ionics.

View Open Roles

Azure Data Engineer

Manchester
3 weeks ago
Applications closed

Related Jobs

View all jobs

Azure Data Engineer

Azure Data Engineer

Azure Data Engineer

Azure Data Engineer - Manchester

Azure Data Engineer - Manchester

Azure Data Engineer...

We’re looking for an experienced contract Data Engineer to join our innovative, fast-growing data team as a Data Engineer and help build the next generation of cloud data architecture on Microsoft Azure. You'll be at the forefront of designing scalable, secure, and modern data platforms using cutting-edge Azure services and the Databricks unified analytics platform.
This is a hands-on engineering role perfect for passionate data professionals who thrive on creating high-performance data infrastructure and solving complex big data challenges in cloud-native environments.  Role will be remote based but may need occasional site visits and work must be conducted from the UK.

What You'll Be Doing
Data Architecture & Engineering

Design and implement enterprise-scale, robust data solutions using Azure and Databricks
Architect scalable ELT/ETL pipelines using Azure Data Factory, Azure Synapse Analytics, and Databricks
Build automated data ingestion processes from various sources including streaming and batch data
Develop and maintain data transformation workflows using PySpark, Scala, and SQL on Databricks
Data Platform & Optimization

Design and optimize Databricks clusters for performance, cost management, and resource utilization
Implement medallion architecture (Bronze, Silver, Gold) for data processing and transformation
Optimize Spark jobs and queries for maximum performance and cost efficiency
Monitor and troubleshoot data pipeline performance issues
Collaboration & Best Practices

Work closely with data scientists, analysts, and business stakeholders to understand requirements
Implement data governance frameworks and ensure data quality standards
Participate in code reviews and maintain high coding standards
Document technical solutions and create knowledge-sharing materials
Essential Requirements
Technical Expertise

4 years of hands-on data engineering experience with strong focus on cloud data platforms
Azure Mastery: Deep expertise in Azure data services including: 
Azure Data Factory
Azure Synapse Analytics
Azure Data Lake Storage
Azure SQL Database
Databricks Proficiency: Advanced skills in Databricks including cluster management and optimization
Programming: Strong proficiency in Python, Scala, and SQL for data processing, transformation, and performance optimization
Big Data Technologies: Proven experience with distributed computing and big data frameworks
Cloud & DevOps

Deep understanding of Microsoft Azure ecosystem and cloud-native data services
Experience with CI/CD practices, Git-based workflows, and Infrastructure as Code
Knowledge of data orchestration tools (Azure Data Factory, Airflow, or similar)
Understanding of Azure security best practices, RBAC, and data encryption
Streaming & Real-Time Processing

Knowledge of real-time data processing using Azure Event Hubs, Kafka, and Spark Streaming
Experience with event-driven architectures and streaming data pipelines
Data Governance

Understanding of data governance frameworks, Unity Catalog, and data quality practices
Experience with data lineage, cataloguing, and metadata management
Desirable Skills

Experience with other cloud platforms (AWS, GCP)
Knowledge of containerization technologies (Docker, Kubernetes)
Familiarity with machine learning workflows and MLOps practices
Experience with data visualization tools (Power BI, Tableau)
Certification in Azure data services

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Seasonal Hiring Peaks for Data Science Jobs: The Best Months to Apply & Why

The UK's data science sector has matured into one of Europe's most intellectually rewarding and financially attractive technology markets, with roles spanning from junior data analysts to principal data scientists and heads of artificial intelligence. With data science positions commanding salaries from £30,000 for graduate data analysts to £140,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this intellectually stimulating and rapidly evolving field. Unlike traditional analytical roles, data science hiring follows distinct patterns influenced by business intelligence cycles, research funding schedules, and machine learning project timelines. The sector's unique combination of mathematical rigour, business impact requirements, and cutting-edge technology adoption creates predictable hiring windows that strategic professionals can leverage to advance their careers in extracting insights from tomorrow's data. This comprehensive guide explores the optimal timing for data science job applications in the UK, examining how enterprise analytics strategies, academic research cycles, and artificial intelligence initiatives influence recruitment patterns, and why strategic timing can determine whether you join a pioneering AI research team or miss the opportunity to develop the next generation of intelligent systems.

Pre-Employment Checks for Data Science Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in data science reflects the discipline's unique position at the intersection of statistical analysis, machine learning innovation, and strategic business intelligence. Data scientists often have privileged access to comprehensive datasets, proprietary algorithms, and business-critical insights that form the foundation of organisational strategy and competitive positioning. The data science industry operates within complex regulatory frameworks spanning GDPR, sector-specific data protection requirements, and emerging AI governance regulations. Data scientists must demonstrate not only technical competence in statistical modelling and machine learning but also deep understanding of research ethics, data privacy principles, and the societal implications of algorithmic decision-making. Modern data science roles frequently involve analysing personally identifiable information, financial data, healthcare records, and sensitive business intelligence across multiple jurisdictions and regulatory frameworks simultaneously. The combination of analytical privilege, predictive capabilities, and strategic influence makes thorough candidate verification essential for maintaining compliance, security, and public trust in data-driven insights and automated systems.

Why Now Is the Perfect Time to Launch Your Career in Data Science: The UK's Analytics Revolution

The United Kingdom stands at the forefront of a data science revolution that's reshaping how businesses make decisions, governments craft policies, and society tackles its greatest challenges. From the machine learning algorithms powering London's fintech innovation to the predictive models guiding Manchester's smart city initiatives, Britain's transformation into a data-driven economy has created an unprecedented demand for skilled data scientists that far outstrips the available talent. If you've been contemplating a career transition or seeking to position yourself at the cutting edge of the digital economy, data science represents one of the most intellectually stimulating, financially rewarding, and socially impactful career paths available today. The convergence of big data maturation, artificial intelligence mainstream adoption, business intelligence evolution, and cross-industry digital transformation has created the perfect conditions for data science career success.