Data Platform Operations Analyst, L1 Production Support

Insight Global
New Miami, OH, United States
8 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Compensation
$104,000 - $124,800
Working hours
Regular working hours
Job source

Tech stack

Java (Programming Language) Batch Processing Data as a Services Data Infrastructure Extract Transform Load (ETL) DevOps Github Nagios Reliability Engineering Kusto Query Language Software Engineering SQL Databases
+8 more
Workflow Management Systems Diagnostic Tools Data Processing Azure Data Factory Grafana Kubernetes Low Latency Cosmos DB

Job description

Work Arrangement: Hybrid, minimum weekly onsite attendance Schedule: Standard Eastern Time business hours + limited weekend critical-incident rotation Pay Rate Range: $50-60/hr, We are seeking a Data Platform Operations Analyst to provide L1 production support for a large-scale enterprise data platform supporting ingestion, ETL/data-processing workflows, Azure Cosmos DB, and downstream data services.

This is an operations/support role, not a software engineering, DevOps, SRE, or infrastructure engineering position.

The analyst will monitor platform health, respond to alerts and routine failures, execute documented recovery procedures, and escalate complex technical problems to engineering. A significant portion of the environment already has engineering-created runbooks, so success requires good troubleshooting judgment and disciplined operational execution rather than deep development expertise.

Key Responsibilities Production Monitoring Monitor dashboards and operational tools to ensure the platform and data-processing workflows remain healthy. Identify failed or stalled ingestion/ETL jobs, abnormal behavior, and production alerts. Perform routine health checks. Review available logs and diagnostic information to understand the nature of a failure. Recognize common data-platform symptoms such as throttling, latency, ingestion failure, or repeated processing errors. Incident Response & Recovery Respond to routine production incidents and operational requests. Follow engineering-provided runbooks to troubleshoot known issues. Restart or retry failed jobs and workflows when documented procedures permit. Validate recovery after taking approved actions. Escalate issues to the Operations Lead or Engineering when documented procedures do not resolve the problem. Gather useful diagnostic information for engineering rather than simply forwarding an alert. Support critical incidents under direction from senior Operations/Engineering resources. Operational Requests Execute routine dataset promotions and other approved production requests. Follow established change controls and operating procedures. Maintain accurate incident and operational records. Support regional handoffs and clearly communicate outstanding issues to incoming teams. Global Support Model Work within a follow-the-sun operating model supporting handoffs between the US, India, and Philippines teams. Provide clear updates at regional shift boundaries. Participate in a limited weekend rotation for major/critical incidents.

Important Scope Boundary

This individual will not be expected to modify application code, infrastructure, AKS/Kubernetes configurations, Cosmos DB configurations, or production pipelines.

Engineering retains ownership of deep troubleshooting, root-cause remediation, platform changes, and technical recovery design. The analyst’s responsibility is to monitor, recognize, triage, execute documented recovery, confirm results, and escalate appropriately.

Schedule / On-Call Standard US Eastern Time business hours. Global handoffs with India and Philippines operations teams. Possible weekend critical-incident rotation, approximately 9 AM to 5 PM ET when assigned. Expected rotation is no more frequent than approximately once every two months. Weekend incidents have historically been rare.

Requirements

3+ years in production application support, data-platform operations, ETL support, batch processing support, or comparable technical operations. Experience monitoring production applications or data-processing systems. Experience responding to failed jobs/workflows and performing documented retries, restarts, or recovery procedures. Familiarity with ETL/data-ingestion workflows and common upstream/downstream dependencies. Ability to use monitoring dashboards, logs, and diagnostic tools to investigate production issues. Strong understanding of incident triage and escalation. Ability to distinguish between an issue that can be resolved through an established runbook and one requiring engineering escalation. Strong communication and documentation skills. Comfortable working independently within well-defined operational procedures. Azure Cosmos DB exposure. Basic understanding of Cosmos concepts such as: HTTP 429 throttling Request Units/throughput Latency Retries Azure data-platform experience. Grafana or comparable monitoring/alerting tools. GitHub Issues/GitHub Actions or comparable workflow tools. ETL/batch processing support. Java application support exposure. AKS/Kubernetes familiarity. SQL or KQL exposure. Experience working in a geographically distributed/follow-the-sun support organization.

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