Sr. Associate, Analytics

LinkedIn•Sunnyvale, CA

5h•$98,000 - $158,000•Hybrid

About The Position

This role will be based in San Francisco. 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. We are hiring a Sr. Associate, Analytics, to own and scale finance reporting through best-in-class data products, governed metrics, and trusted data foundations. This role sits at the intersection of Finance, Analytics, and Technology and operates as a senior individual contributor with high visibility and influence. The ideal candidate brings analytics engineering mindset, strong BI craftsmanship, and the ability to partner closely with Finance stakeholders to deliver executive-ready insights and scalable, self-serve reporting. This is not a dashboard-only role you will build durable, auditable reporting systems that stand up to scrutiny, reduce manual effort through automation, and improve the speed and quality of finance decision-making.

Requirements

Education: Bachelor's degree in a quantitative/technical field (or equivalent practical experience).
Experience: 6+ years in BI/analytics roles delivering business-critical reporting and automation.
Technical proficiency: 4+ years writing advanced SQL (complex joins, window functions, query optimization, data quality checks) and building robust reporting solutions in Power BI, Tableau, Looker, or equivalent.

Nice To Haves

Finance domain fluency: Experience supporting finance stakeholders (close/GL-adjacent reporting, planning inputs, operational finance metrics, governance/controls mindset).
Semantic/modeling depth: Experience designing metric/semantic layers and scalable datasets for self-serve BI.
Certification in Power BI and/or Microsoft Power Platforms with ability to streamline visualization capabilities and drive reporting self-service to key business partners.
Automation & scripting: Python (or similar) for automation, data validation, and repeatable analysis workflows.
Data quality & governance: Familiarity with data lineage, documentation, master data concepts (e.g., cost centers, suppliers, customers, products), and operationalization of standards.
Program leadership: Strong track record managing multi-workstream analytics initiatives with clear milestones, risks, and stakeholder communications.

Responsibilities

Own BI solutions end-to-end: Design, build, and operate finance-facing dashboards, metric layers, and automated reporting.
Build scalable data foundations for reporting: Build data models, semantic layers, and curated datasets that enable consistent finance reporting and automation.
Enable automation at scale: Replace manual reporting with automated pipelines, alerts, and self-serve workflows.
Establish governed metrics & KPI definitions: Partner with Finance stakeholders to standardize definitions (e.g., revenue, expenses, headcount, bookings) and implement consistent logic across reporting surfaces.
Raise the BI bar: Establish best practices for dashboard UX, performance, semantic consistency, documentation, and stakeholder enablement.
Identify automation opportunities: Proactively identify "high-friction" finance processes that can be streamlined through data products.
Drive cross-functional execution: Lead complex, multi-stakeholder initiatives across cross functional teams (setting roadmaps, milestones, and clear success metrics).
Deliver executive-ready narratives: Translate analysis into crisp recommendations; build repeatable "insight-to-action" mechanisms (business reviews, scorecards, operating rhythms).
Enable self-serve capabilities: Champion adoption of BI products and empower Finance partners to make faster, better decisions through training, documentation, and stakeholder enablement.
Drive cross-functional execution: Lead complex, multi-stakeholder initiatives across cross functional teams (setting roadmaps, milestones, and clear success metrics).
Deliver executive-ready narratives: Translate analysis into crisp recommendations; build repeatable "insight-to-action" mechanisms (business reviews, scorecards, operating rhythms).
Enable self-serve capabilities: Champion adoption of BI products and empower Finance partners to make faster, better decisions through training, documentation, and stakeholder enablement.