Senior DataOps Engineer

3 days ago

Leeds, United Kingdom Harnham Full time

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

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