Data Engineer | ETL, SQL, Python, ML, LLM | FTC

Bury St Edmunds
1 year ago
Applications closed

Related Jobs

View all jobs

Machine Learning Operations Engineer

Data Engineer, Data Engineer Data Analyst ETL Developer BI Developer Big Data Engineer Analytics Engineer Data Platform Engineer Cloud Data Engineer Azure Data Engineer Data Integration Specialist DataOps Engineer Data Pipeline Engineer

Quantexa ETL/Scoring Engineer (ML, MLOps, Azure) - London and remote - 11 months +

Senior Data Scientist & ML Engineer (f/m/d)

Lead Engineer, MLOps (London)

Lead Site Reliability Engineer - DataOps

Data Engineer | ETL, SQL, Python, ML, LLM | FTC

We have an exciting opportunity to join a dynamic data programme, embarking on a journey of discovery and delivery to fully leverage data across the organisation. After 30 years of growth and acquisition, our business is now focusing on internal projects aimed at taking stock of our data assets and answering key questions: Where is our data? Who is using it? Where is it going? And what can we do with it?

Duration: This role will be offered as a fixed-term contract, set to run until the end of 2025.

Location: Mid-Suffolk, between Stowmarket and Bury St Edmunds. – Hybrid, 3 days on site

Salary: Dependent on experience, up to £60,000 plus benefits is a guide

Right to work: No sponsorship or transfers will be possible for this opportunity

'We are looking for people with top level SQL, Python, and other data engineering languages. They should have experience of upskilling and coaching other team and programme members. Experience with data engineering common practises and processes such as ETL, MDM, are a must at this stage as the programme is focusing on data cleansing, with a view to bringing in AI/LLM tools in the future. Essentially we are looking for someone to work within a team to embed data foundations, data engineering processes and best practise, were there is currently none.'

Key Responsibilities:

  • Data Preparation and Cleansing: Gather, analyze, and prepare data from a wide range of technology stacks for cleansing.

  • Data Analysis: Interrogate and manipulate data to solve complex business problems.

  • Collaboration: Work with business stakeholders to identify technical requirements and collaboratively design data products to meet business outcomes.

  • Process Establishment: Establish processes for data manipulation to ensure they are repeatable and scalable.

  • Support and Analysis: Assist the programme team with business analysis activities by performing analysis and mining on existing data platforms.

  • Workshop Participation: Participate in data workshops with technical and non-technical stakeholders, confidently presenting findings from data exploration work.

    Required Skills and Experience:

  • Analytical Solutions: Experience in designing and implementing analytical solutions to solve complex business problems.

  • Data Mining Tools: Proficiency with data mining tools and techniques, such as SQL and Python.

  • Large Datasets: Background in working with large and complex datasets, identifying patterns, trends, and insights.

  • Communication: Ability to communicate findings and recommendations to both technical and non-technical stakeholders.

  • Data Privacy: Experience in ensuring data privacy and security, adhering to GDPR standards.

    Ideal (Not Essential) Skills:

  • Database Technologies: Experience with database technologies across multiple stacks, including Microsoft SQL Server, Oracle, and PostGIS.

  • Analytics Tools: Experience working within a data analytics team and utilizing analytics tools (e.g., Power BI).

  • Big Data Technologies: Familiarity with big data technologies such as Hadoop and Spark.

  • Guidance and Support: Experience in providing guidance on new processes and technology to support data roles.

    If this role interests you, please apply.

    Data Engineering | Data Solutions | Data Management | Data Analyst | Data Mining | Business Analyst | ETL | Python | Oracle | SQL | Machine Learning

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.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.

Neurodiversity in AI Careers: Turning Different Thinking into a Superpower

The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus. This guide is written for AI job seekers in the UK. We’ll explore: What neurodiversity means in an AI context How ADHD, autism & dyslexia strengths match specific AI roles Practical workplace adjustments you can ask for under UK law How to talk about your neurodivergence during applications & interviews By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.