Senior DataOps Engineer

CompanyHarnham

LocationLeeds, England, United Kingdom

Posted At12/5/2025

UK Visa Sponsorship Analytics

Occupation Type

IT business analysts, architects and systems designers

Occupation Code Skill LevelHigher Skilled

Sponsorship Salary Threshold

£54,900 (£28.15 per hour)

Occupation rate applies

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Description

Senior Data Ops Engineer

Based: Leeds - hybrid

Salary: up to £62,000

I'm partnered with an established FS company who are scaling their cloud-native data platform and building a modern, centralised data function to better support a wide community of Data Scientists, Analysts, and federated Data Engineers across the organisation.

They are looking for a Senior DataOps Engineer to help shape how data pipelines are run, monitored, governed, and optimised at scale.

This is an opportunity to join a growing team working at the heart of the organisation’s data transformation, improving platform efficiency, enabling self-service, and ensuring data pipelines operate with the same discipline as production software.

The Role

As a Senior DataOps Engineer, you’ll take a strategic, high-level view of the data platform while still diving deep when needed. You will focus on observability, automation, pipeline performance, operational excellence, and cloud cost optimisation.

You’ll work cross-functionally with Data Engineering, DevOps, and FinOps teams, helping ensure that data services are reliable, scalable, secure and cost-effective, and that federated teams across the organisation can self-serve with confidence.

What You’ll Be Doing

Taking an overview of how pipelines run across the platform, improving performance and throughput
Enhancing observability and monitoring across Azure-based data workloads
Identifying bottlenecks and opportunities to streamline operational processes
Using scheduling/orchestration tools to optimise workflows and improve run times
Treating data pipelines like production-grade software with robust monitoring, automation, and scalability in mind
Supporting incident management and helping federated teams resolve issues efficiently
Driving efficiency through automation and reduction of manual operational overhead
Working with FinOps practices to optimise spend and evaluate cost-performance trade-offs
Advocating for better platform usage, adoption, and operational best practices

Tech Stack & Skills

Essential

Strong experience working with Azure cloud platform
Background in data engineering and building/maintaining data pipelines
Experience with pipeline monitoring, observability, and incident troubleshooting
Strong automation mindset and ability to build resilient, self-healing data workflows

Nice to Have

Knowledge of FinOps principles and cloud cost optimisation
Experience with orchestration tools such as Azure Data Factory, Databricks Workflows, or Airflow
Exposure to containerisation tools (Kubernetes, Docker)
Experience with data cataloguing tools
Familiarity with unit testing in data pipelines
Awareness of MLOps practices