Data Engineer

Data Platform Engineer

Automated Incident Detection & Remediation Design and implement automated incident detection and remediation frameworks for data platforms and pipelines. Shift incident response from reactive manual processes to proactive, policy-driven workflows. Improve mean time to detect (MTTD) and mean time to remediate (MTTR) through automation.

DataOps Automation & AIOps Frameworks Build and operationalize DataOps automation frameworks, incorporating AIOps where applicable for anomaly detection and predictive alerting. Reduce operational noise and repetitive manual tasks through intelligent automation. Establish standardized operational runbooks and automated recovery patterns.

Platform Observability & Telemetry Standardization Define and implement platform-wide observability and telemetry standards for data workloads. Enable consistent metrics, logging, alerting, and health signals across platforms and pipelines. Ensure operational visibility is actionable and supports automated response.

Self-Service Operational Tooling Build self-service operational tooling that enables engineering teams to debug, monitor, and resolve issues independently. Reduce operational dependencies on centralized teams and vendors. Empower teams with standardized dashboards, insights, and tooling.

Automated Cost Governance & Optimization Establish automated cost governance and optimization frameworks for data platforms. Improve cost visibility through telemetry, alerts, and policy-based controls. Drive proactive cost management rather than reactive spend reviews.

Required Skills & Experience Strong experience in Data Operations, Data Platform Operations, or SRE/DataOps roles. Proven experience reducing operational toil through automation-first approaches. Hands-on experience with incident management, observability, and operational tooling. Experience operating within or transforming managed services or vendor-led operating models. Strong understanding of cost governance and optimization in data platforms. Hands-on experience with Microsoft Azure data platform services such as Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Microsoft Fabric Experience implementing CI/CD and release automation using Azure DevOps, including Azure Pipelines, repository management, deployment workflows, and environment-based promotion controls. Experience with Microsoft Entra ID, Azure Key Vault, and Microsoft Purview for identity, secrets management, governance, data lineage, and compliance controls. Strong scripting and engineering skills in Python, SQL, and PowerShell to build automation, operational runbooks, telemetry pipelines, and remediation workflows. 5+ years of relevant experience.