Principal Architect, Financial Data Governance
Principal Architect, Financial Data Governance
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Job Description
At LinkedIn our approach to flexible work is centered on trust and optimized for culture connection clarity and the evolving needs of our business. The work location of this role is hybrid meaning it will be performed both from home and from a LinkedIn office on select days as determined by the business needs of the team.
This role will be based in San Francisco or Mountain View CA.
We are seeking a strategic and technically adept Principal Architect to lead the design and execution of our Financial & Corporate Data Governance architecture. As Finance evolves into a data-driven AI-enabled function this role will be foundational in shaping how we govern manage and scale our financial data ecosystem.
This individual will serve as the principal technical expert on data governance within our CFO organization and primary partner for engineering in how we architect our systems - bridging the gap between governance policy business needs and system capabilities. This role defines and advises on the data governance architecture and collaborates with delivery teams on execution. They will be responsible for translating governance objectives into business and technical requirements to drive scalable data architecture working closely with the Director of Finance Tech & Systems Strategy to embed data needs into our financial systems roadmap.
This is a senior individual contributor role that will report into our Finance Data Strategy team and align closely with our Finance Technology and Productivity Engineering partners. This role will not directly own reporting infrastructure or data operations but will work closely with Finance Technology and emerging Data Foundations and Data Triaging teams to ensure governance requirements are embedded into design and execution. The ideal candidate combines deep technical fluency with strong business acumen and a passion for driving clarity across complex enterprise data landscapes.
- Translate financial and operational strategy into scalable business/technical requirements for data governance across key domains (e.g. customer channel product geo etc.)
- Ensure that our data governance architecture aligns with business goals regulatory requirements and analytics use cases while working with Engineering to drive standards across financial and corporate domains including MDM lineage metadata and data quality frameworks.
- Lead the evaluation and adoption of data governance tools MDM platforms and data cataloging solutions that support a federated scalable data ecosystem in partnership with Productivity Engineering & CFO Technology teams.
- Partner with the Director of Finance Tech & Systems Strategy to ensure data governance needs are embedded in our systems strategy and technology roadmap.
- Partner with Data Triaging and Data Foundations teams to ensure technical data challenges and root causes are addressed prioritized and delivered in alignment with governance priorities.
- Collaborate with Finance BPOs Engineering Functional Data Stewards and Analytics teams to align on domain ownership data stewardship and governance policies.
- Develop models and frameworks for managing hierarchies dimensions and reference data used in enterprise reporting planning and analytics.
- Partners with reporting and analytics teams to ensure governed data flows seamlessly into reporting infrastructure (note: provides architectural governance standards but does not own BI/reporting layer directly.)
- Serve as the primary liaison between business teams and engineering partners on governance-related design decisions.
- Champion best practices for data quality access control and lifecycle management within the finance ecosystem.
- Support initiatives that enable AI automation and self-service analytics by ensuring data is reliable accessible and well-governed.
- Support audit readiness compliance and internal control requirements through well-defined ownership data lineage and access standards.
Qualifications :
Basic Qualifications:
- Bachelors degree in Computer Science Information Systems Mathematics Engineering Finance or a related field or equivalent experience.
- 8 years of experience in data governance financial data management data architecture or enterprise systems roles with technical depth including governance platforms and tools.
- 5 years of experience designing and implementing Master Data Management (MDM) metadata management and data governance frameworks.
- 5 years of experience working with finance or corporate data domains governance platforms and tools and how they interact with enterprise systems (e.g. ERP planning procurement HR reporting).
- 5 years of experience translating business strategy and process needs into scalable technical requirements and system designs with a track record of cross-functional collaboration and stakeholder influence across Finance Engineering and Operations.
Preferred Qualifications:
- Masters Degree in Computer Science Information Systems Mathematics Engineering Finance or a related field.
- Experience working within a Finance Enterprise Data or Corporate Systems team in a large or high-growth organization.
- Understanding of how well-governed data enables AI automation and digital workflows in finance and enterprise environments.
- Experience supporting financial data compliance and controls including SOX audit processes and regulatory reporting frameworks.
- Knowledge of enterprise architecture principles data modeling and data integration across SaaS platforms.
- Passion for simplification clarity and enabling teams through better data foundations and governance frameworks.
Suggested Skills:
- Data Governance
- Systems Design and Architecture
- Financial Master Data Management
- Cross-Functional Partnership
LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $149000 to $242000. Actual compensation packages are based on several factors that are unique to each candidate including but not limited to skill set depth of experience certifications and specific office location. This may be different in other locations due to differences in the cost of labor.
The total compensation package for this position may also include annual performance bonus stock benefits and/or other applicable incentive compensation plans. For more information visit Information :
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Employment Type :
Full-time
Employment Type
Full-time
