Production Support Lead - Data

Production Support Lead - Data

We are seeking a highly accountable Production Support Lead to own 24x7 operational stability of the DataONE enterprise data platform. This role will lead onshore and offshore teams (Data Engineering, SRE, Data Quality) to ensure high availability, reliability, performance, and data correctness across a platform powered by Snowflake, Kafka, Oracle GoldenGate, and Java-based microservices hosted on Azure/Kubernetes. The ideal candidate is a strong operations leader with hands-on technical depth, proven incident/problem management, strong stakeholder communication, and the ability to build a mature Ops readiness model (runbooks, SOPs, monitoring, SLIs/SLOs, automation).

Key Responsibilities:

• 24x7 Operations Ownership Own end-to-end production support for DataONE platform with round-the-clock coverage across onshore/offshore teams
• Establish shift model, on-call rotations, escalations, and operational governance
• Ensure adherence to SLAs/OLAs for incidents, requests, data issues, and platform uptime
• Incident, Problem & Major Incident Management Serve as Incident Commander for Severity 1/2 outages and customer-impacting events Drive triage, containment, recovery, and communication cadence (internal + customer).
• Lead root cause analysis (RCA), corrective actions (CAPA), and prevention via automation/engineering fixes
• Implement problem management to reduce repeat incidents
• Observability, Monitoring & Reliability Engineering Partner with SRE team to establish/operate: Platform health dashboards, alerting, and run-time instrumentation Monitoring for Snowflake workloads, Kafka lag, GoldenGate replication, microservices health, Kubernetes, and data pipeline
• SLAs Define and track SLIs/SLOs, error budgets, and availability/performance targets
• Data Correctness & Data Quality Operations Oversee data-quality processes with DQ engineers: Source-to-target reconciliation, anomaly detection, threshold-based alerting Governance of data validation gates before publishing downstream datasets
• Ensure data incident handling is as rigorous as platform incidents (impact, ETA, mitigation, prevention)
• Release, Change & Environment Management Coordinate with engineering teams for release management, change windows, and deployment readiness
• Ensure rollback plans, validation steps, and post-release monitoring are standard practice Manage environment stability across dev/test/prod, access provisioning, and audit readiness
• Runbooks, SOPs & Knowledge Management Build and maintain high-quality operational documentation: Runbooks, SOPs for common tickets, troubleshooting guides, escalation trees Platform known issues registry and operational playbooks
• Ensure continuous knowledge acquisition and reduce dependency on individuals
• Stakeholder Management & Reporting Provide crisp, outcome-driven status to customer leadership: uptime/availability, incident trends, backlog health, repeat issues, MTTR, change success rate Translate technical problems into business impact and propose corrective actions
• Team Leadership & Delivery Excellence Lead and mentor a multi-discipline team: Data Engineers (platform pipelines) SREs (reliability/observability/automation)
• Data Quality Engineers (validation/reconciliation/data incidents) Drive culture of ownership, operational discipline, and continuous improvement

Required Skills & Qualifications:

• Operations / Leadership Strong experience leading 24x7 production operations for enterprise systems/platforms
• Deep knowledge of ITIL processes: incident/problem/change management Proven track record of improving MTTR, reducing repeat incidents, and operationalizing platforms
• Technical (must-have working knowledge) Snowflake: monitoring, performance troubleshooting, workload tuning concepts Kafka: consumer lag, throughput, partitions, operational triage Oracle GoldenGate (or similar replication): monitoring replication health, lag, failure patterns
• Java microservices: logs/metrics/tracing, dependency failures, deployment issues Azure + Kubernetes: container operations, scaling, pod restarts, config/secrets, networking basics
• Strong troubleshooting in Linux, log analysis, and automation (Shell/Python) Communication
• Ability to communicate clearly with non-technical stakeholders
• Strong documentation and executive status reporting skills

Preferred Skills:

• Experience supporting telecom-scale or large enterprise data platforms
• Familiarity with observability tools: Splunk, Grafana, Prometheus, ELK, Dynatrace
• Exposure to data observability/data quality tooling and automated validation frameworks
• Experience running Ops maturity initiatives (SLOs, error budgets, automation-first, self-healing patterns)
• Key Deliverables (First 30-60 Days) Implement 24x7 support model: RACI + escalation + shift/on-call schedule
• Establish operational dashboards and alerts across Snowflake/Kafka/GoldenGate/services Publish runbooks + SOPs for top ticket categories
• Start weekly operational reporting: incidents, MTTR, repeat issues, backlog, release health Define initial SLIs/SLOs and action plan to stabilize key failure areas

TekWissen® Group is an equal opportunity employer supporting workforce diversity.