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- Tasks: Lead data analytics projects and support team development in delivering top-notch services.
- Company: Join an award-winning agency specializing in Data Analytics & Business Intelligence for Media & Sports.
- Benefits: Enjoy flexible hours, remote work options, and a competitive salary of £50,000-£65,000.
- Why this job: Be part of a collaborative culture with vast learning opportunities and a supportive team environment.
- Qualifications: Must have commercial experience as a Data Engineer and advanced skills in Python and data warehousing.
- Other info: Nice to have cloud experience and familiarity with analytics tools like Google Analytics.
The predicted salary is between 40000 - 52000 £ per year.
Senior Data Analytics Engineer | Bristol (Hybrid) | £50,000-£65,000
Peaple Talent have partnered with an award winning Data Analytics & Business Intelligence agency. They provide custom data services that empower industry leading clients across Media & Sports entertainment.
Due to exciting growth plans in the Data team we are now looking for a Senior Data Engineer to inspire and support the teams development in best of class service delivery.
We are looking for:
- A well rounded skillset with exposure to Data Analytics, Visualisation & Reporting
- An excellent communicator and positive, supportive, solution-oriented team player
- A number of years commercial experience as a Data Engineer or relevant role
- Advanced experience using Python
- Data warehouse knowledge such as Databricks and Snowflake
Nice to haves:
- Cloud experience in AWS/Azure/GCP
- Experience using Google Analytics, Adobe Analytics etc.
What's in it for you:
Location: Bristol, flexible hours, remote working
Salary: £50,000-£65,000
Collaborative culture and great team support
Vast L&D opportunities both internally and externally
Senior Data Analytics Engineer employer: Peaple Talent
Contact Detail:
Peaple Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Analytics Engineer
✨Tip Number 1
Make sure to showcase your experience with data analytics and visualization tools during the interview. Be prepared to discuss specific projects where you've successfully implemented these skills.
✨Tip Number 2
Highlight your communication skills by preparing examples of how you've collaborated with teams in the past. This role values a supportive team player, so demonstrate your ability to inspire and motivate others.
✨Tip Number 3
Familiarize yourself with the latest trends in data engineering, especially around tools like Databricks and Snowflake. Being knowledgeable about these platforms will give you an edge in discussions.
✨Tip Number 4
If you have experience with cloud services like AWS, Azure, or GCP, be ready to talk about it. Even if it's not a requirement, showing your familiarity with cloud environments can set you apart from other candidates.
We think you need these skills to ace Senior Data Analytics Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in Data Analytics, Visualisation, and Reporting. Emphasize your commercial experience as a Data Engineer and any relevant projects you've worked on.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention specific skills that align with their requirements, such as your experience with Python and data warehousing technologies like Databricks and Snowflake.
Showcase Communication Skills: Since they are looking for an excellent communicator, provide examples in your application that demonstrate your ability to work collaboratively and supportively within a team.
Highlight Nice-to-Haves: If you have experience with cloud platforms like AWS, Azure, or GCP, or tools like Google Analytics and Adobe Analytics, make sure to include these in your application to stand out from other candidates.
How to prepare for a job interview at Peaple Talent
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Data Analytics, Visualisation, and Reporting. Highlight specific projects where you've used Python and data warehousing tools like Databricks and Snowflake.
✨Communicate Effectively
As an excellent communicator, you should demonstrate your ability to explain complex data concepts in simple terms. Practice articulating your thoughts clearly and concisely.
✨Emphasize Team Collaboration
Since they value a supportive team player, share examples of how you've worked collaboratively in previous roles. Discuss how you’ve inspired or supported your teammates in achieving common goals.
✨Prepare for Cloud Experience Questions
If you have experience with cloud platforms like AWS, Azure, or GCP, be ready to discuss it. Even if it's a 'nice to have', showing familiarity can set you apart from other candidates.
