Enterprise Analytics Production Support Lead

Title: Enterprise Analytics Production Support Lead

Location: South Plainfield, NJ- Hybrid 3 Days Onsite

Job Summary

We are seeking an Enterprise Analytics Production Support Lead to coordinate monitoring, incident response, operational support, and minor enhancements for our AWS-based data lakehouse and related analytics platforms. This individual will coordinate the work of data engineers, help prioritize and track incident response, and coordinate interface with internal business clients.

Key Responsibilities:

• Lead production monitoring and support coordination for the AWS data lakehouse, including pipelines, batch jobs, alerts, incidents, service requests, and data quality issues.
• Provide day-to-day supervision and task coordination for data engineering team responsible for support and minor enhancements.
• Triage production issues, assess business impact, prioritize response, and coordinate resolution across engineering, platform, infrastructure, security, and business teams.
• Monitor and support AWS analytics services including S3, Redshift, and Glue.
• Coordinate root-cause analysis, corrective actions, and preventive improvements for recurring incidents or defects.
• Manage intake, prioritization, assignment, and tracking of minor enhancements and operational improvements.
• Maintain support procedures, runbooks, escalation paths, service expectations, and production readiness checklists.
• Track and report operational metrics, including incident volume, aging, SLA adherence, recurring issues, job failures, data latency, and backlog status.
• Partner with stakeholders to communicate support status, risks, outages, and planned changes.
• Support production monitoring for Power BI Service, including refresh failures, gateway issues, and user-impacting incidents.

Mandatory Qualifications:

• Experience leading or coordinating production support for enterprise data, analytics, or cloud platforms.
• Experience supporting and sustaining data load jobs using Extract, Transform, Load (ETL/ELT) methodologies.
• Experience using Python, SQL, Shell Scripts and AWS Services such as Athena, Glue, Lambda, S3, EMR, Relational Database Service (RDS) and Redshift.
• Experience with data lake house operations, job scheduling, data quality, and production monitoring.
• Ability to supervise and hold accountable contractor resources.
• Experience with incident management, root-cause analysis, change coordination, and operational reporting.
• Strong communication skills, including the ability to explain technical issues, business impact, priorities, and resolution plans.
• Experience managing support queues, operational backlogs, SLAs, runbooks, and escalation processes.
• Ability to balance urgent production incidents with planned enhancements and continuous improvement work.
• Strong analytical, organizational, and follow-through skills.
• Familiarity with enterprise security, access management, data governance, and compliance expectations.

Desired Qualifications

• Experience supporting Power BI Service in an enterprise environment, including dataset refreshes, gateways, workspaces, capacity, permissions, and user support coordination.
• Familiarity with SAP data environments, Simplement, and AWS Sagemaker.
• Familiarity with ITIL practices, including incident, problem, change, and service request management.
• Experience with ServiceNow or similar monitoring, ticketing, and workflow tools.
• Experience creating dashboards or operational reports for platform health, support performance, and service reliability.
• Ability to identify automation opportunities that reduce manual support effort and improve production reliability.