At a Glance
- Tasks: Build and deploy advanced analytical models to provide impactful insights.
- Company: Join SHL, a leader in transforming workplaces with data-driven solutions.
- Benefits: Enjoy a comprehensive benefits package and flexible work environment.
- Other info: Inclusive workplace with opportunities for personal and professional growth.
- Why this job: Make a real difference by improving data products and insights for global clients.
- Qualifications: Proficient in SQL/Python/R with strong analytical and troubleshooting skills.
The predicted salary is between 40000 - 50000 £ per year.
We are hiring for an Analytics Engineer to build, test and deploy advanced analytical models and visualisations to provide insights while producing scalable data products.
What you will be doing:
- Take ownership of building, testing and deploying advanced analytical models and visualisations to provide insights while producing scalable data products.
- Work with internal stakeholders to assess, refine and prioritise analytics use cases and requirements and translate into technical model specifications, including the pricing team, finance team and commercial team.
- Assess SHL’s existing data landscape and leverage it to develop semantic layers and reports and evolve our reporting landscape in line with our business strategy.
- Collaborate with the Business Intelligence team to improve the data landscape and enable faster, more accurate insights through improved data products.
- Build robust end-to-end data products based on strategic semantic layers, balancing speed of delivery and the need for scalable and reliable data engineering.
- Promote optimum practices in data engineering and aid a culture of high‑quality, reliable data across the organisation.
What we are looking for from you:
Essential
- Can translate business needs into technical data requirements and explain to users.
- Proficient in SQL/Python/R or any other pipeline language to produce ETL/ELT flows.
- Root‑cause analysis to test and troubleshoot data solutions using a methodical approach.
- Good awareness of data management and governance.
Desirable
- Machine Learning and statistics experience.
- Experience in agile delivery.
Benefits
- Employee benefits package that takes care of you and your family.
- Support, coaching, and on‑the‑job development to achieve career success.
- A fun and flexible workplace where you’ll be inspired to do your best work.
- The ability to transform workplaces around the world for others.
SHL is an equal opportunity employer. We support and encourage applications from a diverse range of candidates. We can, and do, make adjustments to ensure our recruitment process is as inclusive as possible.
Location: Thames Ditton Office, United Kingdom. Candidate must have the right to work in the UK.
Analytics Engineer in Thames Ditton employer: SHL Group
At SHL, we pride ourselves on being an exceptional employer, offering a vibrant and flexible workplace in Thames Ditton where creativity and collaboration thrive. Our commitment to employee growth is evident through comprehensive support, coaching, and development opportunities, ensuring that you can achieve your career aspirations while contributing to transformative data solutions that impact workplaces globally. Join us to be part of a diverse team that values innovation and inclusivity, making every day at work meaningful and rewarding.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics Engineer in Thames Ditton
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at SHL. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! Prepare a portfolio of your best analytical models and visualisations. When you get the chance to chat with hiring managers, let your work speak for itself.
✨Tip Number 3
Be ready to discuss real-world problems. Think about how you can translate business needs into technical solutions. This will show you're not just a techie but someone who understands the bigger picture.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of the SHL team.
We think you need these skills to ace Analytics Engineer in Thames Ditton
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Analytics Engineer. Highlight your experience with SQL, Python, and any relevant projects that showcase your ability to build and deploy analytical models.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're the perfect fit for this role. Share specific examples of how you've translated business needs into technical requirements and how you’ve collaborated with teams in the past.
Showcase Your Problem-Solving Skills:In your application, don’t forget to mention your approach to root-cause analysis and troubleshooting. We love candidates who can methodically tackle data challenges and come up with effective solutions.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It’s the best way for us to receive your application and get you on our radar quickly!
How to prepare for a job interview at SHL Group
✨Know Your Data Inside Out
Before the interview, dive deep into SHL’s data landscape. Familiarise yourself with their existing data products and think about how you can enhance them. Be ready to discuss specific examples of how you've built or improved analytical models in the past.
✨Speak Their Language
Make sure you can translate technical jargon into business terms. Practice explaining your previous projects in a way that highlights how they met business needs. This will show that you understand both the technical and business sides of analytics.
✨Showcase Your Problem-Solving Skills
Prepare to discuss your approach to root-cause analysis. Think of a time when you faced a data issue and how you methodically resolved it. This will demonstrate your troubleshooting skills and your ability to handle challenges effectively.
✨Collaborate and Communicate
Since collaboration is key in this role, be ready to share examples of how you've worked with cross-functional teams. Highlight your experience in agile delivery and how you’ve contributed to creating a culture of high-quality data within your previous organisations.
