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

Gather and document business and functional requirements, analyze processes, recommend improvements, produce BRDs/FRDs/user stories and process maps, support solution design, UAT, testing and deployment, produce reports/dashboards, monitor project progress, and support change management and stakeholder communication.

Supports a large-scale government data migration from planning through conversion and validation. Analyzes source and target systems, develops conversion scripts, supports API integration, defines data mappings and transformations, and produces stakeholder-ready documentation. Provides recommendations on migration approach and data quality, collaborates with technical and business teams, and validates migrated data for completeness and accuracy. The role is remote within the United States and requires Public Trust or MBI suitability eligibility.

Manage, design, and optimize data activities for federal IAM systems. Develop data models, file layouts, source-to-target mappings, data dictionaries, integrations, ETL processes, and analytics support for identity analysis and fraud detection. Administer and tune databases, including configuration, backups, monitoring, capacity planning, and performance optimization. Support secure handling of identity and PII data, network-related data flows, documentation, token management processes, and collaboration across development, security, and operations teams.

Analyze large healthcare datasets, build and implement quantitative models, perform statistical analyses, ensure data accuracy, collaborate with cross-functional teams, and provide actionable insights to improve healthcare delivery.

Analyze business data, build and maintain business models, provide actionable insights and reports, collaborate with cross-functional teams, monitor performance, and recommend efficiency improvements to support strategic decision-making.

Analyze large healthcare datasets to extract insights, build data models, reports and dashboards, ensure data quality, collaborate with cross-functional teams, and present findings to stakeholders.

Supervises Data Services team focusing on data engineering and operations, ensuring alignment with IT policies, data governance, and operational reliability of data products.

Own end-to-end analytics for the Pro product: build production data pipelines and dbt models, define north-star metrics, design dashboards and full-funnel reporting, lead A/B experimentation and causal inference, embed AI tooling, and deliver clear data-driven recommendations to product and leadership.

Build and own the data platform backbone: design ingestion patterns, Snowflake warehouses, governance, and freshness strategy. Implement reliable batch and streaming pipelines, data quality, observability, and onboarding processes. Lead legacy migrations, create data contracts and SLAs, and apply AI-native tooling to automate debugging, documentation, and operational workflows while partnering with Analytics, Engineering, and vendors.

Lead design and ownership of a modern data platform: ingestion, Snowflake governance, pipeline reliability, migrations, data contracts, observability, and AI-enabled tooling. Partner with Analytics, Engineering, and vendors to deliver trustworthy data products and operate production pipelines.

Own the companys end-to-end data graph, ensure data quality and lineage, and deliver Sigma dashboards and client-facing reports. Act as single owner for triage, prioritization, and translation of business questions into actionable insights, partnering closely with data engineering and business leaders to set standards for production-ready reporting.

Manage daily Data team operations, research and analyze datasets, build internal and external reports (including an annual Startup Ecosystem Ranking), and maintain/improve Python scripts and data infrastructure to deliver actionable insights.

Drive revenue operations analytics by building reliable data models and dashboards, querying large datasets in Snowflake, ensuring data integrity across the revenue tech stack, and delivering strategic insights to Sales, Marketing, and Customer Success using Looker, Domo, SQL, and scripting.