Data Engineer Python SQL AWS SaaS

Client Server
Sunderland
1 month ago
Applications closed

Related Jobs

View all jobs

Bright Data Engineer Needed | London | SaaS | 1st Class STEM Degree

Bright Junior Data Engineers x 2 | London | SaaS Data Platform

Junior Data Scientist | London | SaaS Data Platform

Data Engineer ( Cloud Experience )

AWS Data Engineer

Data Engineer

Data Engineer (Python SQL AWS) Sunderland / WFH to £55k


Are you a data technologist? You could be progressing your career within a relaxed, supportive team environment at a tech driven online gaming / low-cost gambling SaaS tech company that provide a range of white labelled gaming platforms for household names with millions of concurrent players.


You will join a small team of Data Engineers responsible for implementing methods to improve data reliability and quality, combining raw information from a variety of different sources to create consistent and machine readable formats as well as developing the data infrastructure that enables data extraction and transformation for predictive or prescriptive modelling.


You'll have a broad scope of responsibilities including data ingestion, data transformation, data storage, ETL, data modelling, data quality and governance, data integration, performance tuning, scalability, resilience, security, tooling and technology. You'll take a senior role and be able to contribute to continual process and technology improvements.


WFH Policy:

There's a hybrid work from home policy with 2-3 days a week; when you're in the office you'll be collaborating with fellow technologists in a relaxed environment in awesome custom built offices in Sunderland with a range of facilities and perks including free meals at the onsite restaurant as well as membership at onsite gym.


Requirements:

  • You are a Data Engineer with strong experience of data models, data mining and segmentation techniques
  • You have coding skills with Python and / or PySpark and SQL
  • You have experience with SQL databases (e.g. Amazon Redshift, PostgreSQL)
  • You have experience with data tooling (e.g. Airflow, DBT, AWS Kinesis)
  • You have strong analysis and problem solving skills
  • You're collaborative with excellent communication skills


What's in it for you:

  • Competitive salary to £55k depending on experience and knowledge
  • Continual training, learning and career development opportunities
  • Bonus (paid quarterly)
  • Pension
  • Private medical care
  • And a range of other perks and benefits


Apply nowto find out more about this Data Engineer (Python SQL AWS) opportunity.


At Client Server we believe in a diverse workplace that allows people to play to their strengths and continually learn. We're an equal opportunities employer whose people come from all walks of life and will never discriminate based on race, colour, religion, sex, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. The clients we work with share our values.

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.