Staff Software Engineer, Data Governance & Trust
$216,200 - $324,400
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L6
$216,200 - $324,400
Occupations
Computer Systems Engineers/ArchitectsSoftware DevelopersComputer and Information Systems Managers- Set technical direction and deliver shared capabilities
- Shape the architecture and technical roadmap for Data Governance and Trust in partnership with engineering leadership, product partners, domain teams, and governance stakeholders.
- Lead initiatives from discovery and ambiguous requirements through design, implementation, adoption, and ongoing operation.
- Design and build services, integrations, APIs, and automation that connect metadata, ownership, classification, lineage, quality signals, and policy information across the data ecosystem.
- Establish reusable engineering patterns that embed trust requirements into data publishing, discovery, access, consumption, change, and retirement.
- Stay hands‐on through prototypes, production code, design reviews, and the resolution of complex technical problems.
- Lead conversations and build alignment
- Serve as a technical spokesperson for the group in architecture discussions, planning forums, domain engagements, and leadership reviews.
- Facilitate discussions among stakeholders with different priorities, surface disagreements constructively, and guide decisions toward clear outcomes.
- Explain technical choices, business implications, risks, and costs to both engineering and nontechnical audiences.
- Challenge assumptions respectfully, incorporate feedback, and help teams reach workable agreements on standards, ownership, and implementation.
- Document decisions, clarify responsibilities and dependencies, and follow through on commitments across teams.
- Build relationships that enable adoption through credibility, collaboration, and influence.
- Make governance practical and sustainable
- Partner with governance, security, privacy, and domain stakeholders to translate agreed requirements into implementable controls and traceable evidence.
- Help domain teams define data contracts, quality expectations, ownership responsibilities, and lifecycle practices supported by shared platform capabilities.
- Connect quality and reliability signals to accountable owners, consumer communications, and remediation workflows.
- Evaluate build, buy, and integration choices based on interoperability, usability, reliability, operating cost, and long-term flexibility.
- Measure success through improvements in approved data use, adoption, reliability, reuse, and operational effort.
- Prepare the foundation for AI consumption
- Develop ways to make business meaning, provenance, quality status, and permitted‐use information available to applications and AI through supported interfaces.
- Partner with AI and platform teams on governed access to data and context, including traceability and defined behavior when required trust information is missing.
- Support shared semantic definitions and metadata models while preserving clear accountability within business domains.
- Strengthen the team
- Mentor engineers in system design, technical judgment, stakeholder engagement, and leadership.
- Raise engineering standards for reliability, maintainability, testing, observability, and documentation.
- Help engineers take broader ownership and communicate their recommendations effectively.
- What you bring
- A track record of designing, building, and operating production software or data platforms, with demonstrated impact across multiple teams.
- Deep knowledge of metadata management, data governance, lineage, data quality, privacy engineering, access controls, or closely related platform domains, grounded in practical delivery.
- Hands‐on expertise building or extending metadata and catalog platforms such as Atlan, Alation, DataHub, Open
- Metadata, or comparable systems.
- A practical understanding of federated ownership models, data stewardship, semantic models, business glossaries, or certified metrics.
- The ability to work across warehouse, lakehouse, streaming, and data transformation environments.
- Demonstrated delivery of data contracts, automated lineage, quality checks, or policy as code.
- Sound judgment in translating ambiguous business or policy requirements into clear technical designs and delivered outcomes.
- Proven ability to lead initiatives across teams without direct reporting authority.
- Skill in leading difficult technical or organizational conversations, resolving competing priorities, and securing clear decisions and commitments.
- Strong written and verbal communication, including architecture proposals, decision documents, and presentations tailored to different audiences.
- A collaborative approach grounded in listening, respectful challenge, and shared accountability.
- A commitment to mentoring engineers, supported by examples of improving the effectiveness of the teams around you.
- What would be valuable
- Strong software engineering skills, including proficiency in a language such as Python, Java, or Go, and practical SQL experience.
- Experience with distributed systems, APIs, integrations, and cloud data infrastructure, including sound judgment about reliability, consistency, security, and failure handling.
- Experience implementing controls that generate operational evidence.
- Delivering governed data or context services for analytics, applications, machine learning, or AI agents.
- Leading platform adoption, modernization, or migration across organizational boundaries.
- Representing technical work through internal forums, technical writing, communities of practice, or external presentations.
Level
LeadL6
Salary
$216,200 - $324,400
Location
San Mateo, CA
Occupation
Computer Systems Engineers/Architects
Industry
Software Publishers
Posted
yesterday
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