We are hiring a hands-on Service Delivery Manager to run day-to-day production support for our Big Data and data integration platforms. You will lead a support pod of L1/L2/L3 engineers, act as incident commander for critical outages, own SLA delivery, and drive the automation agenda that removes recurring manual work. Key Responsibilities Incident & Problem Management Act as incident commander for P1/P2 production outages drive triage bridges, coordinate cross-team resolution, and manage business communication until service restoration. Own and deliver Root Cause Analysis (RCA) documentation within agreed SLAs; track corrective and preventive actions to closure. Run problem management for recurring issues; convert known errors into permanent fixes rather than repeated workarounds. SLA & Metric Governance Track, report, and enforce response and resolution SLAs across the ticket queue; manage backlog, ageing, and breach risk proactively. Publish weekly and monthly KPI packs MTTR, MTTD, SLA compliance, ticket volume and trend, availability, automation savings to leadership. Own the operational review cadence with business and technology stakeholders. People & Team Leadership Manage 16/7 or 24/7 rotational support rosters, shift handovers, on-call schedules, and holiday coverage. Mentor and coach support engineers; build technical depth and runbook discipline across the team. Conduct performance reviews, goal setting, and development planning; participate actively in interviewing, hiring, and onboarding. Automation & Continuous Improvement Identify high-frequency, high-effort manual tasks and replace them with automation scripts, self-healing routines, and auto-remediation. Improve monitoring and alerting frameworks to shift from reactive to predictive detection; reduce alert noise and false positives. Maintain and continually improve runbooks, knowledge base articles, and standard operating procedures. Cross-Team Collaboration Partner with software engineering, DevOps, and product teams to review upcoming deployments and assess release readiness. Represent support in CAB and change approval forums; enforce operational readiness criteria before production releases. Feed stability pain points, defect trends, and supportability gaps back into the development backlog. Must Have Hands-on experience supporting Hadoop ecosystem components (HDFS, Hive, Spark, YARN, Sqoop, Oozie). Working experience with IBM InfoSphere DataStage — job design, scheduling, failure triage, and performance troubleshooting. Strong Splunk skills — building queries, dashboards, and alerts for log analysis and monitoring. Strong SQL for data validation, reconciliation, and issue investigation. Scripting/programming in Python , Java , or Shell for automation and tooling. ITIL-based Incident, Problem, and Change Management; ServiceNow or JIRA. Linux/Unix fundamentals and job scheduling tools (Control-M, Autosys, Airflow). Good to Have Cloud data platforms (AWS, Azure, GCP), Databricks, or Snowflake. CI/CD and DevOps tooling exposure (Jenkins, Git, Ansible). ITIL v4 Foundation certification.