Data Engineer Data Science/Java/Python/Unix

NLP PEOPLE
London
3 months ago
Applications closed

Related Jobs

View all jobs

Senior Software & Data Engineer (Java/Python)

Software Engineer III- Data Engineer, Java/Python

Senior Big Data Engineer – Scala, Python & Java

Data Engineer

Data Engineer - Proprietary Trading Firm

Data Engineer - Proprietary Trading Firm

Our client is a globally renowned Consumer Electronics brand with a huge online presence and are looking for a Data Engineer to join their small but expanding big data analytics capability based in Central London.

The Data Engineer will be responsible for providing analytical and development services on their large scale data sets with a range of teams on an international scale, complementing their existing SQL and ETL statistical environment. Working closely with the agile data analysis teams, you will need to ensure their reusable data assets build in a regular, efficient manner.

This is an exciting opportunity to join one of the most recognisable technology brands in the world and work with highly complex, large scale data sets and there’s an excellent salary/package on offer. Cornwallis Elt is an Employment Agency and has been listed 3 times in The Sunday Times Virgin Fast Track 100 of the UK`s fastest growing private companies, as well as in the Recruitment International Top 250, Top 50 in IT and the Recruiter Fast 50.

Company:

Cornwallis Elt Ltd (Rec.)

Qualifications:

We are therefore looking for someone with a strong Computer Science or Mathematical background with a proven ability in software development with languages such as Java and/or Python. Working knowledge of Unix environments is required, including Shell Scripting. A passion for learning new languages is vital on top of already advanced SQL skills for data manipulation, ideally with Netezza or a similar technology.

How to apply:

Please mention NLP People as a source when applying

http://www.jobserve.com/gb/en/JobLanding.aspx?jid=927AE0929BB6C157&src=5E0E6ADF4E4799A3&utm_source=00001&utm_medium=Email2014&utm_campaign=JobsByEmailGBR19

Tagged as: Big Data, Data Analysis, Data Mining, Industry, United Kingdom


#J-18808-Ljbffr

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 a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

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

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.