Business Intelligence Engineer

Digital Waffle
Manchester
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Business Intelligence Engineer (Looker)

Senior Business Intelligence Engineer (Looker)

Business Intelligence Developer

French Speaking Finance Analyst

Business Intelligence Manager - Commissioning & ERF

Director Business Intelligence (Basé à London)

This range is provided by Digital Waffle. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

Direct message the job poster from Digital Waffle.

Building Business Intelligence & Data Engineering Teams for Clients in the UK

Location:Manchester (Hybrid)

*Please note, the client doesn’t offer any sponsorship, and will only consider applicants who have the full right to work within the UK.

Do you want to be part of a new exciting project and lead a small Data Engineering team of 8 that's planning to grow through to the organisation's next phase of growth? If so, please carry on reading.

A worldwide innovative and exciting organisation is on the lookout for a Senior Data Engineer/Lead to join their Data team.

This opportunity offers lots of progression and the opportunity to learn and work with the best and newest technologies, and they already have plans to start working with Microsoft Fabric and Machine Learning.

What you’ll do:

  • Support Data Strategy and Architecture: Enable and execute the organization’s Data Strategy, focusing on the development and implementation of robust Data Architecture solutions.
  • Drive Data Platform Solutions: Design and support data platform architecture; evaluate, assess, and estimate new projects and requests.
  • Coordinate Data Engineering Efforts: Lead and support data engineers in addressing challenges related to data ingestion, transformation, and modeling.
  • Streamline Enterprise Data Tools: Collaborate with the Data Governance Board, Digital Council, and IT teams to consolidate enterprise data tools, aligning them to a unified Data Architecture.
  • Collaborate with BI and Data Science Teams: Work closely with business intelligence analysts and data scientists to build and deliver innovative insights and analytics solutions.
  • Enhance Data Literacy: Partner with internal stakeholders and data experts to share best practices and analytics expertise, fostering improved data literacy across the organization.

What we’re looking for:

  • Minimum of 5 years’ experience as a data engineer or a related role.
  • At least 5 years’ experience across key areas such as:
  • Data warehousing, Data Fabric, and Data Virtualization.
  • ETL processes.
  • Business intelligence and advanced analytics.
  • Big data and machine learning (Both desirable, and not essential).
  • Minimum of 2 years’ experience in managing or leading teams.

Technical Skills and Expertise:

  • Advanced knowledge of Cloud Services (preferably Azure) for data engineering, storage, and analytics.
  • Solid expertise in solution architecture and data modeling.
  • Proficiency in programming languages like PySpark or Python.
  • Strong experience with SQL and NoSQL databases.
  • Deep understanding of data warehousing, virtualization, and analytics concepts.

Applying:

If you feel you have the required skills for this opportunity and would like to be considered, please forward an up-to-date version of your CV, and someone will be in contact with you within 24 hours.

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Information Technology

Industries

Staffing and Recruiting

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Jobs

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Jobs Careers

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Jobs

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.