Enterprise Analytics Production Support Lead

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., * 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.

• 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., * 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.