What you’ll do:

If you desire to be part of something special, to be part of a winning team, to be part of a fun team – winning is fun.  We are looking forward to hire FDH Support Leader in Pune, India. In Eaton, making our work exciting, engaging, meaningful; ensuring safety, health, wellness; and being a model of inclusion & diversity are already embedded in who we are - it’s in our values, part of our vision, and our clearly defined aspirational goals. This exciting role offers opportunity to:

The FDH Operations Support Leader is responsible for designing, governing, and operating an end‑to‑end support model for Finance Data Hub products, grounded in DataOps principles. The role owns the definition and execution of tiered SLAs/SLOs, support tiers, and service workflows, ensuring clear accountability across visualization, data engineering, product ownership, and IT teams. Acting as the primary incident leader for critical data outages, the role coordinates cross‑functional response, drives post‑incident remediation, and ensures recurring issues are addressed through runbooks and backlog integration. In parallel, the role champions data observability and proactive operations by establishing monitoring, operational KPIs, and executive‑level reporting to continuously improve reliability, detection speed, and overall support health for finance data products.

Support Model Design & Governance
•    Architect and operationalize a support framework aligned with DataOps principles — embedding quality, automation, and observability from the outset.
•    Define, negotiate, and publish tiered SLAs and SLOs for finance data products covering data freshness, pipeline reliability, dashboard availability, and incident response times.
•    Establish support tiers (L1 through L3) with clear ownership matrices across domain data teams, platform engineering, and vendor partners.
2. Service Configuration & Queue Architecture
•    Partner with the IDM and ITSM teams to design and configure support queues, routing rules, escalation paths, and SLA clocks specific to Finance Data Hub workstreams.
•    Define categorization taxonomies for finance data incidents: user-reported data quality issues, dashboard/BI anomalies, pipeline load failures, schema drift events, and access/entitlement issues.
3. Incident Orchestration & Cross-Team Coordination
•    Serve as the primary incident commander for P1/P2 finance data outages — coordinating rapid response across data engineering, BI/analytics, finance stakeholders, and infrastructure teams.
•    Build and maintain runbooks and playbooks for recurring failure patterns including ETL/ELT load failures, source system latency, model reconciliation breaks, and report refresh failures.
•    Facilitate structured post-incident reviews (PIRs) and drive systemic remediation through backlog integration with data engineering squads.
•    Orchestrate the support interface between finance data domain teams operating as product teams under the data mesh model — ensuring domain SLAs roll up coherently to hub-level commitments.
4. Observability & Proactive Operations
•    Champion data observability across the Finance Data Hub — partnering with data engineering to instrument pipelines, data products, and dashboards with health signals, anomaly detection, and lineage tracking.
•    Establish operational dashboards tracking support KPIs: MTTR, MTTD, ticket volume by category, SLA compliance rate, and repeat incident rate.
•    Drive reduction in Mean Time to Detect (MTTD) through automated monitoring and alerting for system-generated failures (load failures, DQ threshold breaches, schema changes).
•    Lead monthly operational reviews with finance leadership, presenting support health metrics and continuous improvement initiatives."

Qualifications:

Requirement:

• B E/M.Tech in Electrical/Electronics/Computer Sciene
• 12+ years
• 5+ years working with modern data platforms (Snowflake).
• Hands-on familiarity with ELT/ETL pipeline operations, data warehouse concepts, and cloud data infrastructure. Ability to triage data pipeline failures at a technical level.
• 5+ years operating within ITSM framework. Proven experience configuring or governing ServiceNow queues, workflows, and SLA policies. Experience driving knowledge management and deflection strategies.

Skills:

• Demonstrated experience implementing DataOps practices: CI/CD for data pipelines, data quality frameworks, and pipeline monitoring.
• Familiarity with data observability tooling. Understanding of data contracts and SLO definition.
• Track record leading major data incidents — from triage through root cause to PIR. Experience producing incident timelines, stakeholder communications, and systemic remediation plans.
  Strong executive communication skills.
• Proven ability to manage multiple concurrent priorities, build cross-functional alignment, and influence without authority across engineering, business, and IT teams.