Data Engineer

Roles & Responsibilities

Automated Incident Detection & Remediation

Must Have Technical/Functional

Skills:

• Cosmos
• PL/SQL
• MSBI
• Digital :
  Microsoft Power BI
• Digital :
  Big Data Platforms

• 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.
• Data Ops Automation & AIOps Frameworks:
  Build and operationalize Data Ops 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.

• Strong experience in Data Operations, Data Platform Operations, or SRE/Data Ops 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 Dev Ops, including Azure Pipelines, repository management, deployment workflows, and environment-based promotion controls.
• Experience with Microsoft Entra , 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 Power Shell to build automation, operational runbooks, telemetry pipelines, and remediation workflows.
• 5+ years of relevant experience.

• Discretionary Annual Incentive.
• Comprehensive Medical Coverage:
  Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
• Family Support:
  Maternal & Parental Leaves.
• Insurance Options:
  Auto & Home Insurance, Identity Theft Protection.
• Convenience & Professional Growth:
  Commuter Benefits & Certification & Training Reimbursement.
• Time Off:
  Vacation, Time Off, Sick Leave & Holidays.
• Legal & Financial Assistance:
  Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.
• Salary Range: $64,000 - $108,000 a year.