National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

BI & Data Engineering Lead

Delaney & Bourton
Sheffield
5 days ago
Applications closed

Related Jobs

View all jobs

BI & Data Engineering Lead

BI & Data Engineering Lead

Data Engineering Lead

Principal Engineering Lead (Data Products)

Lead Data Engineer

Senior Data Engineer

Role:BI & Data Engineering Lead

Location:Hybrid 2 days in the office, Newcastle

Salary:circa £75k-£80k + Benefits Package


Organisation:


A B2B organisation hugely fuelled by untapped Data with a super impressive Fortune 500 client base, well positioned for future growth and opportunity


Role:


A unique opportunity for someone that enjoys variety and challenge. This role will touch all parts of BI & Data Engineering, from strategy > tooling > architecture > implementation as well as working closely with the organisation to gain more value from unstructured, complex data.


A player/coach role, this role will line manage a small and growing team, as well as keep their hands dirty, specifically with architecture, data engineering (data pipelines, warehouses and transformation logic), as well have accountability for the team that deliver the BI reporting solutions (Power BI) to the organisation


This role will be pivotal in enabling the business to turn data driven decision making into reality. This will result in significant business value and opportunity.


Well suited to someone that see’s a future as a Head of BI & Data Engineering.


Current tech stack is Current set up is - ETL (Azure Data Factory) > DW (Azure SQL) > Data Models (Azure Analysis Services) > Visualisation (Power BI)


Key areas of role include:


  • Ensuring scalable, secure and reliable data and BI architecture, including designing and building robust Data Models that are fit for purpose
  • Support in definition, and delivery of BI and Data roadmap
  • Implementation and refinement of Data Governance
  • Ensure user adoption, and work closely with non-technical stakeholders to gain buy-in
  • Evolving the BI, Data, AI and Analytics landscape (AI/ML)
  • Tool selection, cost management and team management


Experience required:


  • Experience in building and scaling BI and Data Architecture
  • Expertise in modern BI and Data DW platforms such as Snowflake, BigQuery, Redshift, Power BI etc
  • Background in ETL/ELT tooling and Data Pipelines such as DBT, Fivetran, Airflow
  • Experienced in Cloud based solutions (Azure, AWS or Google)
National AI Awards 2025

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.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.

The Ultimate Assessment-Centre Survival Guide for Machine Learning Jobs in the UK

Assessment centres for machine learning positions in the UK are designed to reflect the complexity and collaboration required in real-world ML projects. From psychometric assessments and live model-building tasks to group data science challenges and behavioural interviews, recruiters evaluate your statistical understanding, coding skills, communication and teamwork. Whether you specialise in deep learning, reinforcement learning or NLP, this guide offers a step-by-step approach to excel at every stage and secure your next ML role.