Top Senior Analysis Reporting Jobs in Sacramento, CA

Manage a team of 2–3 analysts while remaining hands-on with SQL, dbt models, dashboards, and complex operational analyses. Lead ambiguous, cross-functional initiatives, deliver recommendations to senior stakeholders, ensure data quality, and improve reporting automation. Partner on AI analytics strategy, data readiness, agent evaluation, and human-in-the-loop governance. Responsibilities include coaching, prioritization, performance management, technical review, KPI development, and operational insights across customer experience, fraud, payments, workforce management, and VIP functions.

Build and operate production pipelines for legal records from PACER, court systems, opinions, PDFs, scans, XML, and HTML. Develop LLM-assisted extraction workflows, validate data quality, optimize SQL, and support RAG and semantic search products. Manage AWS S3 and RDS systems within security guardrails while collaborating with engineering teams. The role requires strong Python and SQL skills, legal data experience, document extraction expertise, and autonomous problem-solving with large, messy datasets.

Leads architecture and hands-on development of scalable data pipelines, governed data models, semantic layers, analytics products, and AI workflows. Writes production SQL and Python, establishes engineering standards, mentors engineers, and drives design reviews. Builds agentic and LLM solutions using retrieval and managed AI services while ensuring data quality, observability, reliability, privacy, and regulatory compliance for PHI and genomic data. Partners with stakeholders, platform teams, and governance forums to deliver trustworthy business solutions.

Leads analytics and data engineering for Sales and Revenue Operations. Builds reporting in Looker and Snowflake, manages CRM data flows into cloud warehouses, establishes transformation and modeling layers, and develops forecasts, scoring, churn, and expansion models. Supports territory, quota, pricing, and revenue-truth initiatives while presenting insights to finance and company leadership.

Analyze product, user, transactional, and repayment data to develop risk and underwriting models, reduce losses and fraud, monitor model performance, and guide product and growth strategy. Build Looker dashboards and LookML models, conduct segmentation and experimentation, measure CAC and LTV, and communicate actionable insights to product, engineering, marketing, finance, and leadership.

Lead ownership and evolution of a Microsoft Fabric-based data platform: design medallion/semantic architectures, build and optimize data pipelines, enable Power BI reporting, support SQL Server performance and API integrations, implement observability with Azure Log Analytics/KQL, and shape the data+AI roadmap.

Leads Wiley Research’s commercial analytics strategy, including KPI frameworks, executive dashboards, competitive intelligence, performance measurement, data governance, and scenario modeling. Advises executive and board-level leaders, aligns Finance and commercial reporting, consolidates fragmented data practices, and builds a trusted analytics capability across global teams. The role also develops analytical talent, drives self-service reporting, and translates complex findings into strategic decisions concerning growth, retention, investment, and market performance.

Leads client measurement strategy, analytics audits, tracking implementations, QA, data modeling, attribution, CRO experimentation, privacy compliance, and migration analytics. Presents actionable findings to clients, partners across delivery teams, and helps grow the agency’s analytics practice through standardized processes, tooling, AI adoption, and sales support.

Own university data integrations from source discovery through validated, signed-off feeds. Build SQL queries and scheduled extracts, model data, support partner upgrades and migrations, translate institutional policies into accurate data feeds, and improve monitoring, documentation, and reusable integration patterns. Collaborate with registrars and database administrators while supporting a named set of university partners. The role requires deep experience with student information systems, including PeopleSoft, and occasional travel for partner onsite engagements.

Designs and maintains scalable data pipelines, warehouse models, and analytics solutions. Builds natural-language data interfaces using GenAI and LLM techniques, optimizes SQL, improves data quality and observability, and supports distributed data platforms on AWS or GCP. Partners with engineering, analytics, business, and product teams, contributes to shared codebases, establishes development standards, and participates in production on-call and incident response.