The Data Operations Support Lead will execute the following responsibilities:
Serve as the primary contract liaison, ensuring execution aligns with strategic goals and overseeing daily operational matters.
Lead daily operations for CMM data platforms, pipelines, integrations, applications, analytics environments, and data products.
Establish and manage procedures for monitoring, incident response, problem management, service requests, maintenance, and releases.
Monitor platform availability, performance, capacity, and pipeline health against SLAs; resolve critical incidents and conduct root‑cause analysis.
Coordinate production support across cloud, data engineering, application, BI/analytics, cybersecurity, and infrastructure teams.
Maintain runbooks, knowledge articles, escalation paths, and system documentation.
Manage RAID logs and perform risk identification, communication, and mitigation.
Oversee operational performance of ETL/ELT pipelines, APIs, CDC processes, integrations, data lakes, and warehouses; address pipeline failures and data quality issues.
Support cloud data platforms in AWS, including analytics and AI/ML services; coordinate upgrades, patching, and environment management.
Support capacity planning, performance tuning, resilience, backup/recovery, and disaster recovery activities.
Partner with Data Governance/Data Engineering to operationalize data quality rules, metadata, lineage, and stewardship processes.
Monitor and remediate data quality exceptions, operational risks, and audit findings.
Promote automation for monitoring, deployments, testing, incident response, and operational reporting; support CI/CD, IaC, observability, and SRE best practices.
Build dashboards and metrics for availability, performance, pipeline health, data quality, and incident trends; identify reliability and efficiency improvements.
Lead incident management for high‑priority issues, coordinate escalations, and facilitate post‑incident reviews.
Support change and release management; assess operational impacts of architecture, application, data, and platform changes.
Lead Data Operations personnel, assign priorities, ensure objectives are met, and mentor team members on operational best practices.
