Global Support Lead - Data and Analytics (End client)

Major / Key AccountabilitiesMain Assignments:

• Lead the global Data & Analytics support function across L1, L2, and L3.
• Manage internal/external support resources, including hiring, training, and performance oversight.
• Define and enforce global support governance for incident, problem, and change management.
• Ensure stability of platforms such as Snowflake, Power BI, DBT, pipelines, and integrations.
• Own the Support Roadmap to improve automation, monitoring, documentation, and KPIs.
• Lead critical incident response, RCA, fix deployment, and stakeholder communication.
• Maintain SLAs, service catalog, escalation paths, and vendor engagement models.
• Serve as key point of contact for business stakeholders on service levels and operational performance.
• Collaborate with Platform, Engineering, Data Quality, and Delivery teams on release readiness and hypercare.
• Deploy new operational capabilities including monitoring tools, automation, and governance processes.

Other Assignments:

• Support global programs requiring operational alignment.
• Provide operational input for platform transformation and architecture evolution.

Measures:

• Platform uptime %, pipeline success rate, BI refresh success.
• MTTA, MTTR, and recurring incident reduction.
• SLA compliance and user satisfaction.
• % incidents resolved at L1/L2 and knowledge base coverage.
• Documentation completeness and governance adherence.

Scope: Global Data & Analytics ecosystem, including:

• Snowflake data platform
• Power BI & Visualization layer
• DBT transformations
• Data pipelines & orchestrations
• API & application integrations
• Data Quality & Monitoring solutions
• Metadata, Glossary, Governance tools

Authority / Decision Making:

• Own the Global Support Roadmap for D&A platforms.
• Define scope and escalation governance for operational support.
• Sign-off operational readiness for releases.
• Recommend vendor tools and operational capabilities.
• Enforce global SLAs and service frameworks.

Challenges:

• Operating across multiple time zones and cultures.
• Managing high‑impact incidents in a dynamic environment.
• Maintaining stability in complex D&A architecture.
• Balancing reactive support with long-term improvements.
• Navigating conflicting stakeholder priorities.
• Driving change adoption for modern data platforms.
• Managing ambiguity due to evolving procedures.

Key Contacts: Internal:

• Data Engineering, Architecture, Data Quality, Visualization, Delivery
• Business Translators / Product Owners
• Regional IT teams and Data Stewards
• Cybersecurity, Integration, and Infrastructure teams

External:

• Third‑party vendors, managed services, cloud providers
• Consulting partners supporting D&A operations