Top Remote Data & Analytics Jobs in San Luis Obispo, CA

Administer and optimize Microsoft SQL Server and Oracle databases in a federal enterprise environment. Responsibilities include installation, patching, monitoring, backup and recovery, performance tuning, access management, security auditing, cloud migration support, SQL development, documentation, ServiceNow incident response, root cause analysis, and on-call support. The role requires at least four years of database administration experience and the ability to obtain Public Trust clearance.

Own the end-to-end architecture and roadmap for MyFitnessPal’s product data stack. Coordinate data engineering, business intelligence, product analytics, and backend teams; establish data movement and standardization practices; lead tool evaluations and platform migrations; implement governance, PII handling, deletion workflows, access controls, and cost optimization; and document architecture standards across the organization.

Leads PBM data integration delivery across claims, eligibility, accumulator, and encounter systems. Profiles and validates data, writes advanced SQL, resolves reconciliation discrepancies, investigates production issues, and partners with engineering on scalable healthcare integration architecture. Owns timelines, risks, vendor dependencies, testing, UAT, migration, rollback planning, executive reporting, and post-deployment support. Requires deep PBM claims-processing expertise, data architecture experience, and hands-on knowledge of ETL, secure file transfer, job scheduling, and healthcare data standards.

Design, develop, and maintain Customer Data Platform solutions and data pipelines to create unified customer profiles, manage identity resolution, enable audience segmentation and activation, ensure data quality and governance, and support integrations with marketing, CRM, and cloud data systems.

Executes eDiscovery analytics and AI-assisted workflows in Relativity and related platforms, including TAR, continuous active learning, generative AI classifiers, validation sampling, statistics, and structured analytics. Maintains accurate matter records, tracking, time entries, audit trails, and quality controls. Provides weekend coverage, monitors request queues, supports deadline-driven projects, documents handoffs, and escalates sensitive issues. The role includes structured training and progression toward an eDiscovery consultant track.

Lead and grow data engineering and analytics engineering teams while overseeing data platform modernization, BigQuery and Looker migrations, reusable dbt models, self-service capabilities, governance, reliability, and data foundations for AI and ML. Partner with technical and business stakeholders to prioritize roadmaps, manage hiring and performance, improve adoption, and protect sensitive healthcare data.

Own executive, board, investor, financial, and operational reporting for leadership. Build scalable dashboards, define consistent KPIs, reconcile data across systems, investigate performance changes, and translate complex business questions into actionable insights. Partner with Strategy, Finance, and senior leaders to automate recurring reporting, improve data accuracy, and support actuals-versus-budget-versus-forecast analysis.

Owns analytics for BILL’s payments products, setting the measurement agenda, defining KPIs and OKRs, building production-grade dbt models, and conducting experimentation and causal inference. Partners with Product, Engineering, Finance, Marketing, and leadership to identify opportunities, improve data quality, automate reporting, and influence roadmap decisions. Presents executive insights and defends metric definitions and recommendations.

Processes client-requested data changes, creates data transfer packages, and writes SQL queries against Microsoft SQL databases. Conducts risk assessments, verifies data updates and transfer datasets, creates stored procedures, monitors data across databases, and supports clinical study implementation. Requires strong attention to detail, documentation, communication, prioritization, and occasional after-hours technical support.

Build customer-facing data products for the single-family rental market. Responsibilities include architecting real estate data models, designing reliable data pipelines and workflows, shaping data platform architecture, establishing engineering standards, and developing real estate domain expertise. The role partners with data science and product teams and requires leadership in scalable data engineering.