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For Companies At a Glance
- Tasks: Lead a team to transform complex data into reliable analytics for business decisions.
- Company: Prominent AdTech firm in Greater London with a focus on innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Make a real impact by shaping the future of data analytics in a dynamic industry.
- Qualifications: Extensive experience in data engineering, strong SQL and Python skills required.
- Other info: Join a collaborative environment with a clear roadmap for career advancement.
The predicted salary is between 48000 - 72000 £ per year.
A prominent AdTech firm in Greater London is seeking an experienced Analytics Engineering Manager to lead its growing analytics engineering function. This role focuses on transforming complex data into reliable and scalable analytics to support business decisions.
You will manage a team, oversee the analytics engineering roadmap, and ensure data quality and governance across platforms.
Ideal candidates have extensive experience in data engineering, strong SQL and Python skills, and the ability to communicate effectively with both technical teams and senior stakeholders.
Analytics Engineering Lead — Data Pipelines & Governance in London employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Engineering Lead — Data Pipelines & Governance in London
✨Tip Number 1
Network like a pro! Reach out to folks in the AdTech space on LinkedIn or at industry events. A personal connection can often get your foot in the door faster than a CV.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those involving SQL and Python. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common analytics engineering scenarios. Be ready to discuss how you've tackled data quality and governance issues in the past.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are proactive and engaged. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Analytics Engineering Lead — Data Pipelines & Governance in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data engineering and analytics. We want to see your strong SQL and Python skills shine through, so don’t hold back on showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you’re the perfect fit for the Analytics Engineering Lead role. Share specific examples of how you've transformed complex data into actionable insights and how you’ve led teams in the past.
Showcase Your Communication Skills: Since this role involves liaising with both technical teams and senior stakeholders, make sure to highlight your ability to communicate complex ideas clearly. We love candidates who can bridge the gap between tech and business!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Harnham
✨Know Your Data Inside Out
Make sure you’re well-versed in data engineering concepts, especially around SQL and Python. Brush up on your knowledge of data pipelines and governance, as you’ll likely be asked to discuss how you’ve implemented these in past roles.
✨Showcase Your Leadership Skills
As a potential Analytics Engineering Lead, it’s crucial to demonstrate your ability to manage a team effectively. Prepare examples of how you’ve led teams, resolved conflicts, and driven projects to success. This will show that you can handle the responsibilities of the role.
✨Communicate Clearly with Stakeholders
Since the role involves liaising with both technical teams and senior stakeholders, practice explaining complex data concepts in simple terms. Be ready to share how you’ve successfully communicated insights to non-technical audiences in the past.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about challenges you’ve faced in data quality and governance, and prepare to discuss how you approached these issues and what the outcomes were.
