Data Lead

Roche•South San Francisco, CA

1d•Onsite

About The Position

This role is responsible for owning and governing the US Finance data domain, ensuring that finance data across reporting, planning, analytics, and automation is accurate, standardized, and trusted. It oversees enterprise-level finance data assets, including master data, reporting definitions, hierarchies, semantic layers, and data quality controls that support executive reporting and AI-driven use cases. The role balances strategic responsibilities—such as designing the data governance model, aligning with data architecture, and defining the roadmap—with operational execution, including monitoring data quality, triaging issues, coordinating remediation, and supporting data stewardship. It also drives the adoption of modern data governance practices, embedding a data product mindset, automated quality controls, lineage transparency, and strong metadata discipline to enable scalable analytics and AI readiness across the organization.

Requirements

Bachelor’s degree in Information Systems, Data Management, Finance, Accounting, Analytics, or a related field; Master’s degree (MBA/MS) preferred.
8–12+ years of experience in data governance, finance systems, or reporting/data management roles.
Proven experience establishing or maturing data governance frameworks, including stewardship models and operating structures.
Hands-on experience designing and implementing data quality controls, monitoring, and remediation processes.
Experience working in ERP environments (SAP/S4 preferred) and supporting enterprise reporting ecosystems.
Experience managing or leading small teams or functional stewards (1–2+ individuals).
Experience enabling analytics or AI initiatives with well-governed, high-quality datasets.
Strong understanding of finance data domains (e.g., GL, cost centers, master data, planning structures) and ability to work with SQL or query data independently.
Strong root-cause analysis, structured thinking, executive communication, and disciplined documentation with the ability to translate business KPIs into clear, governed data definitions.

Nice To Haves

Data governance or data management certification (e.g., DAMA/CDMP or equivalent) strongly preferred; training in internal controls or regulatory data standards is a plus.

Responsibilities

Define data governance model: Establish and maintain the finance data domain ownership and stewardship structure across the organization.
Set data standards: Define and maintain KPI definitions, hierarchies, naming conventions, metadata, and the finance data dictionary.
Ensure data consistency: Align data across ERP systems, reporting tools, dashboards, and AI/analytics datasets to maintain a single source of truth.
Oversee data lineage: Document and maintain end-to-end data lineage to support transparency, traceability, and audit readiness.
Drive data quality management: Implement data quality rules, monitoring dashboards, and controls to proactively identify and address issues.
Manage issue remediation: Define exception handling processes, lead root cause analysis, and track resolution of recurring data defects.
Lead cross-functional collaboration: Partner with IT Data Engineering, Enterprise Architecture, BI teams, and global data governance to align on standards and implementation.
Support analytics and AI enablement: Ensure high-quality, reliable datasets are available for reporting, insights, and AI/ML use cases.
Develop and lead the team: Manage and coach a data specialist, setting priorities, driving accountability, and building governance discipline.
Influence stakeholders: Engage finance, IT, and governance partners to drive adoption of standards, resolve trade-offs between speed and data integrity, and promote a culture of data ownership.