Data Engineer

Evesham
2 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Annual Salary: Up to £60,000
Location: Evesham, Worcestershire
Job Type: Full-timeJoin our client's team as a Data Engineer, where you will play a crucial role in developing, building, and maintaining robust data pipelines to enhance business operations. This position offers the opportunity to collaborate across departments, ensuring the availability and integrity of data, and driving actionable insights to support strategic initiatives.

Day-to-day of the role:

Data Infrastructure & Pipeline Development:

Develop and maintain efficient and scalable data pipelines and ETL processes.
Ensure data quality, consistency, and reliability through robust validation and monitoring frameworks.
Collaborate with the team to design and optimise data storage solutions.
Data Integration & Automation:

Automate data ingestion and transformation workflows to enhance efficiency.
Implement best data architecture and governance practices.
Work closely with IT and third-party providers for seamless data integration.
Troubleshoot and resolve issues related to data pipelines and performance.
Collaboration & Stakeholder Engagement:

Engage with stakeholders to understand data requirements and deliver solutions.
Support the delivery of insights and analytics to inform business decisions.
Assist in the optimisation of business intelligence tools to enhance data accessibility.
Innovation & Continuous Improvement:

Stay updated with emerging technologies and best practices in data engineering.
Participate in initiatives to continuously improve data management and reporting.

Required Skills & Qualifications:

Strong experience in Data Engineering, with a solid background in data architecture and ETL pipeline development.
Proficiency in SQL, Python, and experience with cloud platforms like AWS, Azure, or Snowflake.
Understanding of data modelling, database management in ERP and CRM systems, and data warehousing concepts.
Experience with business intelligence and data visualisation tools (e.g., Tableau, Power BI) is desirable.
Excellent problem-solving skills and a methodical approach to safety.
Strong communication skills, capable of explaining complex data concepts to non-technical stakeholders.
Ability to work both independently and collaboratively in a fast-paced environment.Join our client's team and enjoy working in an environment that encourages innovation and offers numerous opportunities to contribute directly to the executive leadership team and progress your career. At our company, we are committed to creating an equitable and inclusive workplace for a diverse workforce.

To apply for this Data Engineer position, please submit your CV and cover letter detailing your relevant experience and why you are interested in this role

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.