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

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.

Document and reverse-engineer the client's ServiceNow data model and ITSM/CMDB processes. Design API-based incremental extraction into a Bronze layer and specify Bronze->Silver->Gold mappings. Define DNA crosswalk keys, data-quality gates and KPI confidence scoring, and support pipeline development, observability, and automated testing for ServiceNow as a source system.

As a Senior Data & Analytics Engineer, you'll lead data initiatives, manage a team, and ensure data quality while turning insights into actionable decisions across the company.

Own client-facing analytics and attribution: establish baselines, implement tracking and lead-to-sale matching, run holdout and lift experiments, quantify cost avoidance, build cross-client benchmarks, and translate findings into clear ROI narratives that inform pricing, product, and renewal conversations.

Transform commercial, market, consumer, and portfolio data into actionable insights. Build and maintain dashboards and KPI reporting, analyze performance and competitive trends, support pricing, assortment, and launch decisions, and deliver executive-ready recommendations while partnering with cross-functional teams to ensure data quality and commercial alignment.