Hybrid Data Reliability Engineer – Observability & Quality

Ashdown Group; England; Hybrid; GBP 45,000 - 65,000; Full time

Job summary

Ashdown Group is seeking a Data Engineer to join their data team in Central London. This hybrid role allows for 2 days of work from home each week.

You will focus on improving data quality, building observability across data platforms, and ensuring data reliability end-to-end. Ideal candidates will have strong skills in SQL and Python, along with experience in cloud-based data environments and observability tools.

Qualifications

• Excellent SQL and Python skills.
• Experience with data observability and governance tools.
• Hands-on experience in cloud-based data environments.
• Proactive problem-solving skills.

Responsibilities

• Improve data quality and reduce incidents.
• Build scalable observability across data platform.
• Define and manage data SLAs and SLOs.
• Implement automated validation and observability tooling.

Skills

SQL

Python

Data observability tools (Grafana, Monte Carlo, Acceldata)

Data governance/quality platforms (Informatica, Collibra, Microsoft Purview)

CI/CD and Infrastructure-as-Code

Tools

Azure ecosystem (data lakes, ETL/ELT pipelines)

Job description

A successful multinational technology business is looking for a Data 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 excellent SQL and Python skills coupled with 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 and observability tooling, and lead root cause analysis when issues occur.

You’ll also have experience building automated data validation frameworks, defining SLAs/SLOs, and working with distributed data architectures. Familiarity with CI/CD and Infrastructure-as-Code is beneficial. Most importantly, you’re a proactive problem-solver who enjoys working collaboratively and improving systems at their root cause.

If you’re looking to take ownership of data reliability in a complex enterprise environment and make a real impact on how data is trusted and used, apply today for immediate consideration.