Top Remote Data Management Jobs in San Luis Obispo, CA

Lead Finance Data & Analytics to build trusted data sources, governance, and analytics for Finance and cross-functional stakeholders. Manage analysts, drive data strategy and Snowflake data models, produce insights via SQL and Tableau, and deploy AI solutions to optimize finance decision-making and operations.

Manage Finance-focused data products, collaborating with teams to define requirements and drive delivery for financial analysis and reporting.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

Lead and scale enterprise data governance operations: manage the data domain model and business glossary, run governance council operations, enforce data policies and compliance (SOC 2, GDPR/CCPA), drive catalog adoption and data literacy, and measure governance maturity and ROI through dashboards and remediation workflows.

Oversee data ingestion and transformation, manage finance data sources, ensure scalability and reliability of data platforms, and collaborate with stakeholders to align data engineering with organizational goals.

Lead and manage a team of data engineers to develop and maintain data pipelines and warehouses, ensuring data quality and adherence to best practices.

Lead a team delivering actuarial, regulatory, and operational statistical reports and analytics. Ensure compliance with bureau submissions, drive reporting automation, define data requirements, lead UAT for policy/claims systems, and manage vendor and regulator interactions to support pricing, reserving, underwriting, claims, and financial analytics.

Lead a data engineering team building and operating NPR's data warehouse, pipelines, BI, and personalization systems. Responsibilities include people leadership, hiring, cross-functional collaboration, Agile delivery, technical design and code review, automation for developer experience, incident response, and vendor management.

Lead a small data engineering team partnering with Engagement Marketing to build scalable ETL/ELT pipelines, ensure data quality, define marketing metrics, integrate trusted data with ad platforms, and drive the data roadmap to enable measurement and growth.

Lead design and build of a cloud-based data platform; manage and mentor data engineering staff; define engineering standards, data governance, and access controls; partner with stakeholders to deliver scalable, reliable data pipelines and platform services for analytics and AI.

Lead a Salesforce data engineering team to design, deliver, and support Salesforce-to-Salesforce integrations and migrations, data modeling, ETL/transformations, automation, and observability. Manage hiring, performance, and career development; partner with stakeholders; adopt AI/LLM agent tooling to automate workflows and improve data quality; reduce technical debt and document systems and processes.

Lead a hands-on data engineering team to build and scale production data pipelines, datasets, and observability for alternative-data products. Drive architecture, data modeling, QA, and AI-ready dataset design while coaching engineers, partnering with product and research, and owning operational excellence across Databricks, Airflow, SQL, and PySpark.

Manage CVS Health's data partnerships and monetization strategy, source new partnerships, ensure operational success, and drive data product adoption across analytics teams.

Serve as the analytics bridge between marketing/operations and data teams: translate business questions and KPIs into clear product requirements, own delivery of treated tables, semantic layers, reports and dashboards, align stakeholders on a single source of truth, run gap analyses, document processes, and ensure delivered data products drive decision-making and adoption.

Lead renewals forecasting, predictive churn modeling, and impact measurement for CX. Build production-grade SQL models in Snowflake, integrate multi-source systems (Salesforce, Gainsight, Gong), apply LLMs/AI to automate workflows, drive data governance, and translate insights for executive decision-making to improve GRR and NRR.

Lead enterprise data strategy and governance, build AI-ready data infrastructure and BI systems, own SharePoint platform, partner cross-functionally to ensure data quality, access, compliance, and user adoption.

Manage day-to-day execution of regional assessment builds and readiness operations in Renaissance (Illuminate) DnA, maintain data quality and compliance, coordinate vendor data collection, develop documentation and training, support regional stakeholders, and continuously improve assessment and data workflows to ensure timely, accurate reporting.

Lead and develop a team delivering enterprise data engineering, analytics, and governance. Oversee data pipelines, ETL/ELT, cloud platforms, integration services, and stakeholder engagement to enable data-informed decision-making across the university system.

Analyze medical claims (inpatient, outpatient, SNF, rehab, professional, DME) to identify utilization and root causes. Pull/integrate data, perform QA, present findings, maintain attribution methodology, coordinate stakeholders, and develop tools. Primary coding: Hive, SQL, Python.

Lead a team of ~7 data scientists to deliver timely, accurate product analytics and experimentation insights; manage people, mentor staff, partner with product and engineering, and build accessible data products and measurement practices.

Own and scale the finance and accounting data ecosystem: design and maintain BigQuery integrations, ensure data integrity and governance, build reconciliations and automated controls, develop scalable reporting and dashboards, support monthly close, forecasting, budgeting, and automate finance processes to improve visibility and efficiency.

Lead a team of data engineers and analysts, define the data engineering roadmap, oversee data infrastructure, ensure analytics delivery, and establish data governance standards.

Manage client-facing data and analytics projects: define data strategy, build automation and ETL, develop visualizations and predictive analytics, drive transformation, manage scope/budget, and communicate findings to non-technical stakeholders while leveraging finance knowledge.

The Exposure Data Manager leads analytics to understand exposure patterns, enforces data standards, ensures data quality, and collaborates across departments for effective exposure management.

Manage and grow a data engineering team, overseeing the design and maintenance of data platforms using Snowflake, dbt, and Azure. Drive best practices in data management and ensure reliable data movement and quality.