Senior Data Engineer

Bolton
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer | Outside IR35 | Remote

Senior Data Engineer - MS Fabric - Remote - £70k - £75k

Senior Data Engineer - DV Cleared

Senior Data Engineer - Snowflake - £110,000 - London - Hybrid

Senior Data Engineering Consultant

Senior Data Engineer - Greater Manchester

An exciting opportunity has arisen for a Senior Data Engineer to join my client’s dynamic and growing data team. In this role, you will work across the full data lifecycle—streaming, enrichment, and curation—within a cloud-based environment. You will be responsible for ensuring data quality, integrating key data sets, and supporting the insights and data science teams.

As part of this role, you will also develop your expertise in Artificial Intelligence (AI) and Machine Learning (ML), with access to advanced training in ML Ops. Additionally, you will play a key role in mentoring and developing junior data engineers.

Key Responsibilities:

Automate and maintain data pipelines within a cloud-based environment (AWS/GCP/Azure).

Source and verify data from multiple sources, ensuring it is ready for ingestion.

Gain experience in data infrastructure and contribute to the development of new cloud-based methodologies.

Analyse large datasets using Python and SQL.

Set up new pipelines for data streaming, enrichment, and curation.

Manage and maintain source code repositories (GitHub).

Investigate and apply AI/ML solutions to enhance cloud capabilities.

Key Skills & Experience:

Strong proficiency in SQL and Python.

Experience in cloud data solutions (AWS, GCP, or Azure).

Experience in AI/ML.

Experience with PySpark or equivalent.

Strong problem-solving and analytical skills.

Excellent attention to detail.

Ability to manage stakeholder relationships effectively.

Strong communication skills and a collaborative approach.

Why Join Us?

Work with cutting-edge technologies in cloud data engineering and AI/ML.

Opportunity for career growth and professional development.

Be part of an innovative and forward-thinking data team.

If you are a motivated Senior Data Engineer with a passion for cloud technologies, AI, and data analytics, we’d love to hear from you.

Interested? Please Click Apply Now!

Senior Data Engineer - Greater Manchester

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.

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.

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.

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.