Top Remote Data & Analytics Jobs in Sacramento, CA

Maintain and monitor Snowflake data warehouse and ingestion pipelines. Troubleshoot file/load/data quality issues, operate SFTP/drop-zone/file automation, support scheduled loads, build dbt models and tables, document runbooks, and serve as backup for core warehouse operations while collaborating with engineering and IT.

Reverse-engineer Procore data model and REST APIs; map Bronze→Silver→Gold datasets with transformation rules and data-quality defects; define crosswalk keys (global Project ID) reconciling Procore, P6, and Yardi; define data-quality gates and confidence scoring; support pipeline development and automated testing; validate Gold datasets against sources and document a reusable template.

Lead enterprise analytics architecture and strategy across Epic Cogito, BI tools, and cloud platforms. Design scalable, secure solutions, enforce RBAC and DevOps/CI-CD practices, mentor federated teams, guide tool selection, and ensure alignment with business priorities. Provide architectural oversight, stakeholder consultation, and adoption planning for analytics initiatives in a large healthcare system.

Lead design and scaling of ELT pipelines and analytics schemas on Snowflake. Build Looker views, CI/CD automation, and orchestration workflows (Prefect/Airflow). Ensure production reliability with monitoring (Datadog, Monte Carlo), partner with cross-functional teams, and provide technical leadership including code reviews, testing, and end-to-end ownership of data integrity and platform trustworthiness.

Analyzes complex claims data to create SQL- and Power BI-based dashboards, reports, scorecards, forecasts, and actionable insights. Identifies claims leakage, payment anomalies, fraud indicators, reserve activity, and operational inefficiencies. Partners with Claims Operations, IT, Data Engineering, and leadership to improve reporting reliability, business performance, and decision-making. The role also supports statistical analysis, reporting governance, and AI-assisted analytics initiatives.

Design and govern conceptual, logical, and physical enterprise data models supporting analytics, reporting, AI-ready datasets, and certified data products. Translate business requirements into scalable data structures across customer, product, payer, and territory domains. Establish modeling standards, review models against Common Data Model standards, maintain metadata and lineage accuracy, and resolve data gaps and inconsistencies. Collaborate with business, engineering, and technology stakeholders to provide modeling expertise and design guidance.

Designs and builds scalable, reliable, observable batch and streaming data pipelines and models. Partners with stakeholders on data integration, validates data quality, writes tests, participates in code reviews, documents solutions, troubleshoots production issues, and aligns technical work with business needs. The role requires strong programming, database, data modeling, governance, and Databricks knowledge, with preferred experience in Spark, AWS data services, CI/CD, testing, orchestration, and transformation frameworks.

Own GTM reporting and analytics across Salesforce, warehouse systems, Tableau, and Excel. Build trusted dashboards, define metrics, investigate data quality issues, and lead analysis for pipeline, forecasting, territory design, capacity planning, productivity, and resource allocation. Partner with GTM, CRM, Data, and Systems stakeholders to improve reporting architecture and support leadership decisions. Use AI tools to automate analysis and develop internal analytics workflows.

Audit and improve human and model-generated data outputs for accuracy, consistency, and policy compliance. Provide actionable feedback, clarify evolving guidelines, support annotators, coach new team members, monitor workflows and blockers, identify recurring issues and edge cases, participate in calibration discussions, and document findings to improve team performance and quality at scale.

Research, annotate and structure financial data from public filings using proprietary tools; standardize and maintain databases, ensure data integrity, collaborate on reporting requirements, and support special projects. Role requires attention to detail, ability to handle high-volume quarterly periods (overtime eligible), and strong Excel skills.