62396 - Data Engineer

Career Moves
Southend-on-Sea
1 week ago
Applications closed

Data Engineer

Location: UK, Remote
Length: 12 Months
Start Date: ASAP
Rate: from £37.02 - £41.35 p/h (Inside IR35)
Hours: 9am-6pm
Interview: 45 minutes coding interview along with 30 minutes screen


Overview:

Data Engineer with at least 4 years of experience in designing and maintaining data pipelines, ensuring data quality, and supporting data analytics. Develop products and get services from the Telcom who serves and strengthen the relationship X4 different products the team works on, and will be allocated to each product based on their skill set.

Key Responsibilities:
 
Data Infrastructure Development 

  • Design, build, visualize, and maintain scalable data pipelines and ETL processes. 
  • Collaborate with the team's engineers to integrate new data sources. 


Data Analytics Support 

  • Work with data scientists to provide clean, reliable datasets for reporting and analysis. 
  • Develop and maintain dashboards and visualizations as needed. 


Data Management 

  • Ensure data quality, consistency, and accessibility 
  • Implement data governance best practices. 
  • Support the team's on-call duties. 


Expected Outcomes 

  • Improve the team's data-driven decision-making capabilities. 
  • Streamlined data processes and reduced manual intervention. 
  • Enhanced data accessibility and usability for the Partner Group team


Top three non – negotiable skills:

  • SQL
  • Python
  • Ability to process and visualise data



Day to Day activities:
 

  • CW will have a project to work on with a clear timeline and interact with data and software POCs to achieve, clear scope and guidance on what is needed and timelines  
  • Communicate clearly  
  • Communicate timelines, raise flags for any concerns  
  • Highly technical delivery’s
  • Most cases are to develop data pipeline processes and data sets to drive decision making for the product team  
  • Backfilling data, building dash boards  
  • Present data. 
  • Working on x1 project at a time and smaller additional tasks if needed – micro deliveries or tasks.  
  • Measure success – Tasks or projects will be well defined with deliverables and need to work towards them, High quality solutions and will be defined. 



Qualifications:

  • At least 4 years of experience in data processing (ETL), data analysis (writing SQL queries), and data visualization, along with a basic understanding of Python programming. 




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

How to Write a Winning Cover Letter for Machine Learning Jobs: Proven 4-Paragraph Structure

Learn how to craft the perfect cover letter for machine learning jobs with this proven 4-paragraph structure. Ideal for entry-level candidates, career switchers, and professionals looking to advance in the machine learning sector. When applying for a machine learning job, your cover letter is a vital part of your application. Machine learning is an exciting and rapidly evolving field, and your cover letter offers the chance to demonstrate your technical expertise, passion for AI, and your ability to apply machine learning techniques to solve real-world problems. Writing a cover letter for machine learning roles may feel intimidating, but by following a clear structure, you can showcase your strengths effectively. Whether you're just entering the field, transitioning from another role, or looking to advance your career in machine learning, this article will guide you through a proven four-paragraph structure. We’ll provide practical tips and sample lines to help you create a compelling cover letter that catches the attention of hiring managers in the machine learning job market.

Jobs Careers

Veterans in Machine Learning: A Military‑to‑Civilian Pathway into AI Careers

Introduction Artificial intelligence is no longer relegated to sci‑fi films—it underpins battlefield decision‑support, fraud detection, and even supermarket logistics. The UK Government’s 2025 AI Sector Deal forecasts an additional £200 billion in GDP by 2030, with machine‑learning (ML) engineers cited as the nation’s second most in‑demand tech role (Tech Nation 2024). The Ministry of Defence’s Defence AI Strategy echoes that urgency, earmarking £1.6 billion for FY 2025–28 to embed ML into planning, logistics, and autonomous systems. If you have ever tuned a radar filter, plotted artillery trajectories, or sifted sensor data for actionable intel, you have already worked with statistical modelling—the backbone of machine learning. This guide shows UK veterans how to reframe military experience for ML roles, leverage MoD transition funding, and land high‑impact positions building the models shaping tomorrow’s defence and commercial landscapes. Quick Win: Bookmark our live board for Machine‑Learning Engineer roles to see who’s hiring today.

Jobs

Rural-Remote Machine Learning Jobs: Finding Balance Beyond the Big Cities

Over the past decade, machine learning (ML) has transformed from a niche research domain into a pervasive technology underpinning everything from recommendation systems and voice assistants to financial forecasting and autonomous vehicles. Historically, the UK’s major tech hubs—particularly London—have been magnets for top ML talent and corporate headquarters. However, remote work has become mainstream, and many ML professionals are realising they can excel in their field while living far beyond the city limits. At MachineLearningJobs.co.uk, we’ve observed a growing interest in positions that allow for a rural lifestyle or a coastal environment, often reflected in search terms like “ML remote countryside” or “tech jobs by the sea.” This surge is no coincidence. Flexible work policies, better rural broadband, and the nature of machine learning tasks—much of which can be done through cloud platforms—are bringing new opportunities to those who wish to swap urban hustle for fresh air and scenic views. Whether you’re a data scientist, ML engineer, researcher, or product manager, a rural or seaside move could reinvigorate your work-life balance. In this article, we’ll unpack why rural-remote ML jobs are on the rise, how you can navigate the challenges of leaving the city, and what you need to do to thrive in a machine learning career beyond the M25. If you’ve dreamt of looking up from your laptop to rolling fields or ocean waves, keep reading—your rural ML role might be closer than you think.

🍪 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.