At a Glance
- Tasks: Ensure data quality and reliability across a modern enterprise data platform.
- Company: Join a successful multinational tech business in Central London.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Collaborate with teams to shift towards a proactive data reliability approach.
- Why this job: Make a real impact on data-driven decision-making in a dynamic environment.
- Qualifications: Experience in Data Engineering or SRE roles with strong SQL and Python skills.
The predicted salary is between 60000 - 80000 £ per year.
A successful multinational technology business is looking for a Data Reliability Engineer to join its growing data team in Central London. This role is hybrid; you'll be able to work from home 2 days per week.
This is a high-impact role focused on improving data quality, reducing incidents, and building scalable observability across a modern enterprise data platform. You'll help ensure data across the organisation is accurate, reliable, and trusted for critical business decision-making.
You’ll take ownership of data reliability end-to-end, designing and implementing frameworks that monitor data health, detect anomalies, and enforce standards across complex data pipelines and platforms.
You’ll have experience in Data Engineering, Data Platform, or SRE-style roles, with strong SQL and Python skills and experience working in modern cloud-based data environments. Hands-on experience with data observability tools such as Grafana, Monte Carlo, or Acceldata, and data governance/quality platforms like Informatica, Collibra or Microsoft Purview is highly desirable. Experience within the Azure ecosystem (data lakes, ETL/ELT pipelines) would be a strong advantage.
Working across Data Engineering and Data Governance teams, you’ll help shift the organisation from reactive issue resolution to a proactive, reliability-led approach. You’ll define and manage data SLAs and SLOs, implement automated validation.
Data Reliability Engineer employer: Ashdown
Join a leading multinational technology business in Central London, where innovation meets collaboration. As a Data Reliability Engineer, you'll thrive in a dynamic work culture that prioritises employee growth and offers flexible hybrid working arrangements. With access to cutting-edge tools and a commitment to data excellence, this role provides a unique opportunity to make a significant impact while enjoying a supportive environment that values your contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Data Reliability Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that Data Reliability Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your SQL and Python projects. We want to see how you tackle data quality issues and build observability frameworks. It’s a great way to stand out!
✨Tip Number 3
Prepare for those interviews! Brush up on your knowledge of data governance tools and cloud environments, especially Azure. We recommend practising common interview questions related to data reliability and incident management.
✨Tip Number 4
Apply through our website! We’ve got loads of opportunities waiting for you. By applying directly, you’ll be in the best position to showcase your passion for data reliability and your fit for the team.
We think you need these skills to ace Data Reliability Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in Data Engineering and any relevant tools like SQL and Python. We want to see how your skills align with the role, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about data reliability and how you can contribute to our team. Keep it engaging and personal – we love a bit of personality!
Showcase Relevant Experience:When detailing your past roles, focus on your hands-on experience with data observability tools and cloud-based environments. We’re keen to see how you’ve tackled challenges in previous positions, especially in relation to data quality and governance.
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 gives you a chance to explore more about our company culture!
How to prepare for a job interview at Ashdown
✨Know Your Data Tools
Familiarise yourself with the data observability tools mentioned in the job description, like Grafana and Monte Carlo. Be ready to discuss how you've used these tools in past roles to improve data quality and reliability.
✨Showcase Your SQL and Python Skills
Prepare to demonstrate your SQL and Python expertise during the interview. You might be asked to solve a problem or explain how you've used these languages to build scalable data solutions in previous positions.
✨Understand Data Governance
Brush up on data governance principles and platforms like Informatica and Microsoft Purview. Be prepared to talk about how you’ve implemented data standards and ensured compliance in your past work.
✨Be Proactive About Reliability
Since this role focuses on shifting from reactive to proactive approaches, think of examples where you've anticipated data issues before they became problems. Share how you’ve defined and managed SLAs and SLOs in your previous roles.
