Data Engineer - 12 FTC

SuccessFactors
Greater London
8 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

At Sephora, beauty is about feeling seen, valued, and empowered, individually and collectively. It is connecting deeply with others, celebrating diversity and inclusivity, unlocking your potential and making a difference every day. Together, we belong to something beautiful.

The Opportunity

At Sephora, data is more than just numbers, it’s the foundation of every strategic decision we make. We’re looking for a Data Engineer to join us on a 12-month fixed-term contract (maternity cover) and play a pivotal role in building and maintaining the data infrastructure that powers our insights. You’ll be instrumental in developing our data warehouse and enabling seamless data flow across the business, empowering teams with the tools they need to make data-driven decisions.

You’ll collaborate closely with our Business Intelligence and Analytics teams to design and implement robust data pipelines, optimise cloud performance, and ensure the integrity and security of our data. Your work will directly support the delivery of key business metrics and help shape the future of data at Sephora.

We’re open to candidates based in either London or St Helier, Jersey, and are happy to explore a flexible working arrangement. 

 

You Will Also Be Responsible For

  • Designing, building, and maintaining scalable data pipelines and architecture
  • Assembling large, complex datasets that meet functional and non-functional business requirements
  • Collaborating with BI and Analytics developers to deliver actionable insights
  • Automating manual processes and optimising data delivery for performance and scalability
  • Supporting the extraction, transformation, and loading (ETL) of data from diverse sources using SQL and GCP technologies
  • Ensuring data security and separation across systems and teams
  • Monitoring and optimising cloud query and storage costs

 

What You’ll Bring

 

You’re a problem-solver with a passion for clean, efficient data systems. You bring a strong foundation in SQL, Python, and cloud-based data architecture, and you’re comfortable navigating both structured and unstructured data environments. You’re proactive, detail-oriented, and thrive in a collaborative setting where your work has a direct impact on business outcomes.

Your experience in data warehousing, ETL development, and cloud technologies enables you to build solutions that are not only technically sound but also aligned with business goals. You’re confident working independently, yet always ready to contribute to a team effort.

 

Our Ideal Candidate Will Also Possess

  • Strong Python skills, with experience pulling data from APIs
  • A solid understanding of Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) database structures (MSSQL and BigQuery preferred)
  • Experience in data warehouse development and design (BigQuery preferred)
  • Proficiency in ETL tools such as SSIS, Talend, or Airflow
  • Familiarity with BI tools like Power BI, Qlik Sense, or Looker (Power BI preferred)
  • Excellent SQL query writing skills
  • Exposure to cloud architecture and SaaS frameworks
  • Excellent problem-solving and decision-making skills
  • Ability to work both independently and collaboratively
  • Experience with machine learning modelling in Python or R is an added bonus

 

Here, you will find:

  • Community, in which authenticity is embraced, and the strength of our differences fuels our collective spirit.

  • Culture of empowerment, learning & growth, that offers you the tools, space and opportunity to learn, innovate and lead

  • Work that brings, fulfillment. From delighting clients every day, to inspiring our industry at large, every action makes a difference

 

Join us and belong to something beautiful.

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.

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

Jobs

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

Education

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

🍪 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.