Analytics Engineer in Devon

Analytics Engineer in Devon

Devon Full-Time 50000 - 60000 Β£ / year (est.) No working from home possible
Virgin Media

At a Glance

  • Tasks: Design and build data pipelines to support analytics and product development.
  • Company: Join giffgaff, a unique mobile brand owned by Virgin Media O2.
  • Benefits: Enjoy competitive salary, flexible working, and a vibrant community culture.
  • Other info: Diverse team culture with excellent growth opportunities and a commitment to inclusion.
  • Why this job: Make a real impact in a tech-driven environment focused on community and sustainability.
  • Qualifications: 3+ years in data engineering, strong SQL skills, and experience with cloud platforms.

The predicted salary is between 50000 - 60000 Β£ per year.

Job Description hackajob is collaborating with Virgin Media to connect them with exceptional professionals for this role. Want to make an application Make sure your CV is up to date, then read the following job specs carefully before applying. Job title : Analytics Engineer Full time / part time / job share : Full time Job Family : Technology Location : Uxbridge with flexibility to work from home Our wonderful gaff is located in Uxbridge, in leafy West London. But if commuting to that part of the country isn't warming your cockles - please don't be put off from applying for this role. The world has changed - particularly when it comes to ways of working. Most of our roles can be on a work from home basis if needed, but we'll ferry you in a few times a year from wherever you are in the UK for team or company days, or our famous giffgaff summer and Christmas celebrations. Who we are : giffgaff is a little different to your 'normal' telecoms company. We're a mobile brand owned by Virgin Media O2 but run by our members (what we call our valued customers) and we've been awarded Uswitch Network of year for 6 years out of 7! Sounds interesting so far? There's more. The word giffgaff is an ancient Scottish word for "mutual giving". Since we were founded upon the principle of putting community first, it's always been our aim to do right by the planet and the people that live on it. We started wanting to change the mobile industry, and we did - offering value, flexibility and mutuality - but we aren't done yet . As we've grown over the years, we've grown our vision too. We believe it's our responsibility to make sure that: ● Keeping people connected doesn't damage the planet ● Everyone can be connected, so everyone gets the same opportunities ● The connections we make online improve our lives Our business model is unique. We take a highly collaborative approach to any decision we make - working with our members (who are rewarded for helping) across all areas of the business. Our vibrant community, online platform and immense value proposition are key to our success. We're both proud and humbled to say that over the past few years our member base has grown, but our job is far from done. We're always looking to acquire new members - but to do that we need the best people to help and that's why we're hiring! The role and the team : We are looking for a skilled Analytics Engineer to join our team and help build and maintain robust data pipelines that support our analytics applications. The Data Engineering team has recently undergone a technology transformation to migrate from our legacy data warehouse to a brand-new data platform (Snowflake + dbt + Argo Workflows + Kafka) to better enable the exciting needs of our data stakeholders (Data Science, Machine Learning and Business Intelligence, etc.). Having built a strong technology foundation, we are now looking for ways to improve the value that we deliver to our data stakeholders. The ideal candidate will have a strong background in data engineering, analytics and be proficient in designing, building, and deploying scalable data pipelines. Product analytics is the practice of using data to inform decision-making related to user behaviour, product development and improvement. As an Analytics Engineer, you will work closely with the Data Science, Product teams and Business teams to build data pipelines and analytical products to support self-serve analytics, data-driven experimentation in Product Engineering. Diversity and inclusion are a priority for us and we are making sure we have lots of support for all of our people to grow at giffgaff. Data and software engineering is at the heart of what we do here at giffgaff - our agile engineering teams build and support a set of applications and services that combined create our unique user experience on the giffgaff website, enable our internal teams to work in the most productive and efficient ways and enable a whole range of awesome features via modern APIs, events and microservices. We have a culture of building and owning all the code that we use, and take pride in this. This allows us to keep full control on what's going on and how we shape solutions. Key responsibilities : ● Design and implement robust data models (e.g., star schema, snowflake schema, data vault). ● Develop and maintain dimensional data models to support BI and reporting requirements. ● Develop and implement analytics solutions to track key performance metrics ● Design and build data pipelines to collect, process, and store large volumes of structured and unstructured data from various sources. ● Develop and maintain data quality checks and data validation processes. ● Develop and automate reports, dashboards, and data visualisations to communicate insights and trends effectively to stakeholders. ● Build and maintain tooling and frameworks to automate data pipelines for experimentation and ML modelling ● Develop and maintain a deep understanding of product domains to ensure relevant events are produced and new entities and processes are integrated downstream in the Snowflake data platform model ● Monitor and troubleshoot data pipeline issues and provide timely resolution. ● Work closely with product managers, data scientists, product analysts and software engineers to identify analytical requirements. Skills, experience and attitudes : Must have: ● Bachelor's degree in computer science, engineering, mathematics, or a related field. ● 3+ years of experience in data/analytics engineering with a focus on building data pipelines. ● Proficiency in SQL and experience with one or more programming languages such as Python, Java. ● Experience with modern cloud data warehouse platforms such as Snowflake, BigQuery, Redshift or similar. ● Experience with cloud-based data platforms, particularly AWS or GCP. ● Experience with data warehousing, data modelling, and ETL development. ● Strong analytical & communication skills and an understanding of what drives the performance of a product to reach the company's commercial goals. ● Hands-on experience with data visualisation tools such as Tableau, Looker, Streamlit or Power BI. ● Strong problem-solving skills and attention to detail. Valuable skills: ● Previous experience in similar analytics engineering roles with focus on product analytics and data modelling is highly desirable. ● Experience working with distributed event stores and stream-processing platforms such as Kafka of Kinesis. ● Experience working with batch processing frameworks, such as DBT, Argo Workflows, Apache Airflow, etc. ● Familiarity with Docker, Kubernetes, Amazon EKS ● Familiarity with Continuous Integration with GitHub Actions ● Familiarity with Test-Driven Development and XP Our commitment to equity, diversity and inclusion : At giffgaff we want to challenge the old way of doing things. People, and the way they work, define our culture and we encourage everyone to bring their whole selves to the gaff. That's why we believe in creating an equitable, fairer, more inclusive business that champions different ideas and perspectives. We may be sort-of-small but we're big on that caring, sharing thing & strive to create a supportive culture. As a lean organisation, our team is built of a diverse, spirited range of people who are multi-skilled, highly motivated and flexible. In return for your outstanding efforts, you'll be rewarded with a competitive salary and excellent benefits. xohmjla We believe that hard work should be supported and recognised.

Analytics Engineer in Devon employer: Virgin Media

Virgin Media in Park Central is an exceptional employer, offering a dynamic work culture that prioritises innovation and collaboration. Employees benefit from comprehensive professional development opportunities, competitive compensation, and a commitment to work-life balance, making it an ideal environment for those looking to make a meaningful impact in the field of Business Continuity and Disaster Recovery.

Virgin Media

Contact Details:

Virgin Media Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land Analytics Engineer in Devon

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Some tips for your application 🫑

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Virgin Media. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Virgin Media

✨Brush Up on Your Statistics

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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

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✨Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.