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- Tasks: Design and maintain data systems to collect, process, and analyse large volumes of data.
- Company: Join a global brand focused on innovation and positive societal impact.
- Benefits: Flexible working, private healthcare, competitive pension, and 26 days holiday.
- Why this job: Be part of a multicultural team transforming customer experiences with cutting-edge data solutions.
- Qualifications: Experience in data engineering, strong SQL skills, and familiarity with cloud platforms.
- Other info: Dynamic environment with excellent career growth opportunities and a focus on diversity.
The predicted salary is between 51000 - 59000 £ per year.
Our client is moving towards the next phase of customer experience – evolving to delivering integrated journeys that meet customer needs traversing both online and offline channels. The Data Engineer will design, build, and maintain the infrastructure and systems required to collect, process, store, and analyse large volumes of data. This role will also be responsible for identifying key data sources within different systems.
As Data Engineer, you will:
- Collaborate with cross-functional teams to understand data requirements, translating these into technical solutions.
- Design and implement efficient and scalable data pipelines to collect, process, and transform raw data into usable formats for analysis and consumption.
- Build and maintain data warehouses, data lakes and data lakehouses that function as repositories for both structured and unstructured data.
- Ensure data quality, reliability, and accessibility.
- Develop data models and schemas that optimise data storage, retrieval, and querying performance.
- Integrate data from numerous sources (databases, APIs, streaming platforms, and third‑party systems).
- ETL (extract, transform, and load) data into appropriate data structures and formats.
- Leverage tools and technologies such as Apache Spark, Hadoop, cloud‑based solutions including data virtualisation and data semantic layers.
- Implement processes and checks to ensure data accuracy, consistency, and compliance with regulatory requirements.
- Identify and resolve performance bottlenecks in data processing and storage.
- Optimise query performance and ensure scalability.
- Monitor data pipelines and systems, troubleshoot issues, and perform routine maintenance tasks (backups, upgrades, and patching).
- Identify and implement data engineering best practices, standards, and processes.
- Ensure thorough data governance and security.
- Stay up to date with emerging data technologies and trends, evaluating their potential application.
- Document system designs, processes, and workflows to facilitate knowledge sharing and maintain a robust data infrastructure.
We would like you to have:
- Proven experience as a Data Engineer or Data Analyst with strong SQL experience (other programming language – Python, Scala, Java – is beneficial).
- Confidence in building data virtualisation layers and data semantic layers.
- Strong knowledge of relational databases (MySQL, PostgreSQL), experience with data warehousing concepts and tools (Snowflake, Redshift), data lakes and data lakehouses.
- Familiarity with distributed computing frameworks like Apache Hadoop, Apache Spark, and NoSQL databases (such as MongoDB, Cassandra).
- An understanding of data modelling techniques (relational, dimensional, and NoSQL) and proficiency in designing efficient and scalable database schemas.
- Experience with workflow orchestration tools (Apache Airflow, Prefect) and data pipeline frameworks (Apache Kafka, Talend).
- Familiarity with cloud platforms (AWS, GCP or Azure) and their data services (AWS Glue, GCP Dataflow) for building scalable cost‑effective data solutions.
- Knowledge of data quality assessment and governance practices, including data profiling & cleansing.
- Knowledge of privacy and security regulations.
- Excellent problem‑solving, communication, and collaboration skills (essential).
The perks:
- The chance to develop your career with a global, multicultural team working on a fascinating customer experience transformation programme.
- A flexible working environment and the ability to work from home / flexible hours.
- Private healthcare and private dental insurance.
- Competitive pension, 26 days holiday (excluding bank holidays).
- Car lease scheme, season ticket loan and cycle to work schemes.
Data Engineer employer: Match Digital
Contact Detail:
Match Digital Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow data enthusiasts on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving data pipelines or cloud solutions. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common data engineering scenarios and be ready to discuss how you've tackled challenges in past projects.
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find roles that match your skills and interests. Plus, it shows you're serious about joining our awesome team!
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Engineer role. Highlight your experience with SQL, data pipelines, and any relevant technologies like Apache Spark or Hadoop. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how you can contribute to our client's mission. Keep it concise but impactful – we love a good story!
Showcase Your Projects: If you've worked on any cool data projects, make sure to mention them! Whether it's building data warehouses or optimising data pipelines, we want to know what you've done and how it relates to the role.
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, we love seeing candidates who follow the process!
How to prepare for a job interview at Match Digital
✨Know Your Data Tools
Make sure you’re well-versed in the tools and technologies mentioned in the job description, like Apache Spark, Hadoop, and cloud platforms. Brush up on your SQL skills and be ready to discuss how you've used these tools in past projects.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled data-related challenges in previous roles. Be specific about the problems you faced, the solutions you implemented, and the outcomes. This will demonstrate your analytical thinking and ability to collaborate with cross-functional teams.
✨Understand Data Governance
Familiarise yourself with data quality assessment and governance practices. Be prepared to discuss how you ensure data accuracy and compliance with regulations. This shows that you take data integrity seriously, which is crucial for a Data Engineer.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s data strategy and the role's responsibilities. This not only shows your interest but also helps you gauge if the company culture aligns with your values, especially regarding diversity and innovation.