At a Glance
- Tasks: Lead the design and delivery of scalable data solutions using cutting-edge GCP technologies.
- Company: Join LiveScore Group, a leader in sports media and betting innovation.
- Benefits: Enjoy flexible working, private healthcare, performance bonuses, and more.
- Other info: Collaborative culture with opportunities for mentorship and continuous learning.
- Why this job: Make a real impact on sports fans' experiences while advancing your career.
- Qualifications: Significant experience in data engineering with strong SQL and Python skills.
The predicted salary is between 60000 - 75000 £ per year.
- Soho, London
- Hybrid working: 3 days in the office Tues - Thurs
The Role
We are seeking a Senior Data Engineer to join our Data Team, taking a leading role in building the complex, scalable systems that power our data strategy.
You will lead architectural discussions, own the design of business-critical data solutions and deliver high-quality systems that bring millions of fans closer to the sports they love.
This is a fantastic opportunity to lead the optimisation of our data platforms for real-time AI/ML workloads, mentor engineers and make a significant impact on our business.
The Senior Data Engineer leads technical initiatives, maintains data integrity and performance, and works across teams to translate complex business requirements into effective data solutions.
The role also uses automation and artificial intelligence to improve efficiency, decision-making and productivity across the organisation.
At Live Score Group, we’re the proud home of three of the most exciting brands in the sports and gaming world: Live Score, Live Score Bet and Virgin Bet.
A fully owned and operated ecosystem that converges the two worlds of sports media and sports betting.
We’re proud of the high ratings for our commitment to excellence and fueling fan’s passion for sport driving us to the top.
We don’t just lead; we innovate.
Our cutting-edge products and immersive experiences set the standard, but it’s our people who truly make the difference.
Every day, our team embody our values: adaptability, teamwork, a fan-driven approach, and an ever-curious mindset that fuels our ambition.
As we scale and continue to create a culture that allows all employees to thrive, we know we need the most talented people with diverse backgrounds, perspectives and skills.
If you’re good at what you do, come and join us.
The more inclusive we are, the more amazing experiences we can create for our users.
We know that job descriptions can sometimes seem daunting, and you might not feel you tick every box.
But, if you’re passionate about the role and have relevant experience, we want to hear from you!
Key Responsibilities
- Lead the design and delivery of robust data pipelines using GCP services such as Big Query, Dataflow, Pub/Sub and Cloud Storage.
This includes integrating data from various sources, ensuring data quality and enabling real-time processing capabilities.
- Own the design of data models and databases that support business analytics and intelligence, using dimensional data-modelling principles.
Select and use GCP database technologies such as Bigtable, Spanner or Firestore to optimise performance and scalability.
- Lead the automation of data workflows and optimisation of data storage and processing costs within GCP.
Use tools such as Cloud Composer for orchestration and establish best practices in performance tuning.
- Ensure data security by implementing GCP security practices. Manage access controls, comply with data-governance policies and safeguard sensitive information.
- Work closely with data engineers, business analysts and IT teams to define data requirements and deliver comprehensive data solutions.
Provide technical leadership and guidance to team members.
- Evaluate new GCP features and data-engineering technologies, setting technical direction where they can enhance data infrastructure or enable new data products.
- Lead the resolution of critical pipeline failures and data-quality incidents, performing fault analysis and ensuring that preventative improvements are implemented.
- Lead critical system-design and architectural decisions for scalable batch and real-time workloads.
- Partner with cross-functional teams to translate complex or ambiguous business needs into effective and innovative data solutions.
- Mentor engineers, review technical designs and foster a culture of continuous learning and engineering excellence.
- Own improvements to the reliability, performance and cost-effectiveness of data systems.
- Lead the design and maintenance of robust, secure integrations with core internal systems and critical third-party platforms.
- Define appropriate monitoring and alerting standards to ensure high system reliability and minimal downtime.
Skills, Knowledge and Experience
- Significant experience in data engineering or data warehousing with large-scale, complex datasets.
- Advanced SQL and Python skills, with experience using AI-assisted development tools appropriately.
- Strong knowledge of data-modelling techniques.
- Deep experience with cloud data services and technologies, ideally within the GCP ecosystem, such as Dataflow, Pub/Sub, Big Query or Vertex AI.
- Proven experience designing and implementing robust ELT pipelines, including real-time and large-scale batch processing.
- Proven ability to deploy and maintain data infrastructure using Infrastructure as Code principles and tools such as Terraform.
- Experience with Airflow environment management and Docker.
- Experience contributing to an AI roadmap and evaluating AI tooling, including coding agents, for use within the development lifecycle.
- The ability to explain complex technical concepts clearly and concisely to technical and non-technical stakeholders.
- Demonstrable experience applying data-governance, privacy and security best practices in a regulated environment.
- A proactive and curious approach, with the ability to anticipate and resolve system inefficiencies.
- The ability to lead cross-functional technical work and translate complex or ambiguous requirements into robust data solutions.
- A track record of taking end-to-end ownership for the quality, reliability and performance of business-critical data solutions.
- Experience mentoring engineers and influencing technical standards across a team.
What can we offer?
- Company Performance Bonus
- Flexible Working Agreements where applicable
- Private Healthcare Scheme + Employee Enhanced Assistance
- Enhanced Family Leave - Maternity, Shared Parental & Adoption Leave: up to 6 months at full pay and 6 months at half pay. Paternity leave: up to 4 weeks at full pay
- Subsidised Gym Membership
- Annual Travel Card Loan & Ride to Work Scheme
- Life Assurance (x3 salary)
- Contributory Pension Plan
- Virgin Family: Giving you access to exclusive Virgin offers and experiences
- Thursday drinks in the office and regular socials
- #J-18808-Ljbffr
Senior Data Engineer employer: Livescore9
As a Player Protection Analyst at our company, you will be part of a supportive and dynamic team dedicated to ensuring the safety and well-being of our members. We offer a flexible hybrid working model after your initial training period, alongside a range of benefits including private healthcare, generous family leave policies, and a performance bonus. Our work culture prioritises employee growth and well-being, making it an excellent place for those passionate about making a positive impact in the gambling industry.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Livescore9!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Data Engineer at Livescore9.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Livescore9.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Data Engineer at Livescore9, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Senior Data Engineer
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!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Livescore9, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Livescore9. 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 Livescore9
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
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!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Livescore9!
✨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.
