Data Reliability Engineer

Key Responsibilities:

• Own and improve the reliability, availability, observability, and operational supportability of Maximus UK's Azure Databricks platform, Azure data services, and associated data pipelines and data products.

• Design and implement monitoring, alerting, health checks, and diagnostics across Azure Databricks, Azure data services, orchestration layers, storage, and downstream consumption, extending these patterns into AWS as the estate grows.

• Define and maintain reliability standards, controls, operational runbooks, and support models that improve the resilience, predictability, and supportability of data services.

• Work closely with data engineering teams to identify, prioritise, and remediate reliability, performance, and data quality issues across Databricks notebooks, jobs, workflows, and other Azure data workloads.

• Establish proactive incident detection, triage, and root cause analysis practices, reducing mean time to detect and mean time to recover for data-related issues.

• Design and implement robust data quality controls, validation frameworks, reconciliation processes, and anomaly detection approaches across the end-to-end data lifecycle.

• Configure and use Azure Purview to provide effective data cataloguing, lineage, ownership, and governance, ensuring reliability and quality controls are visible and auditable.

• Collaborate with platform, cloud, architecture, and security teams to ensure the data estate is secure, resilient, cost-effective, and aligned to enterprise standards and patterns.

• Contribute to the reliability engineering approach for an Azure-first data platform while supporting reusable patterns and operational readiness for data services in AWS.

• Partner with architects and engineers so that new pipelines, data products, and platform services are designed with operability, recoverability, scalability, and observability built in from the start.

• Automate repetitive operational tasks, environment checks, dependency verification, failure handling, and recovery processes to increase efficiency and reduce manual intervention and risk.

• Capture lessons learned, codify reliability patterns and standards, and share best practice to continuously improve reliability, transparency, and engineering discipline across the data function.

Essential Skills - What You'll Bring

• Proven experience in data engineering, platform engineering, site reliability engineering, DataOps, or a closely related role focused on data platform reliability and operations.

• Strong hands-on experience with Azure-based data platforms, particularly Azure Databricks and core Azure data services such as Data Lake Storage, Data Factory/Synapse, and analytical stores, with familiarity of equivalent services in AWS.

• Strong understanding of modern data platform architectures, including data lakes, warehouses or lakehouses, orchestration frameworks, transformation pipelines, streaming ser...