Top Data & Analytics Jobs in Santa Cruz, CA

Design, build, and maintain scalable data pipelines, data models, and analytics solutions using Microsoft Fabric and Azure. Develop Lakehouse and Warehouse architectures, Fabric Notebooks with PySpark and Spark SQL, ETL/ELT workflows, and Power BI semantic models. Optimize performance, ensure data quality, security, governance, and regulatory compliance, and collaborate with analysts, data scientists, and business stakeholders to support business intelligence and advanced analytics.

Clean and reconcile employee master data and historical leave records from multiple sources. Define standardized HR data structures, establish validation and access controls, and automate leave request, approval, and balance tracking workflows using Google Workspace or a suitable alternative. Document maintenance processes and support potential expansion across international branches. The contractor will independently manage the fixed-scope project, propose an RFQ, and provide timeline, hours, costs, assumptions, and deliverables.

Leads enterprise Snowflake architecture, administration, governance, security, performance, and cost optimization across AWS and Azure. Manages Snowflake administrators and data engineers, serves as Product Owner, and leads delivery for federal and public-sector clients. Responsibilities include stakeholder management, technical escalations, data integration, agile backlog prioritization, risk and SOW management, and executive engagement.

Own go-to-market funnel reporting, dashboards, data quality, and analysis for Sales, Marketing, and RevOps. Integrate CRM and marketing data, monitor lead scoring and attribution models, investigate funnel performance, identify root causes, and provide actionable recommendations. Maintain reporting systems, audit data hygiene and tool adoption, and communicate insights clearly to non-technical stakeholders in a remote-first SaaS environment.

Develop customer analytics that improve retention, growth, adoption, and operational performance. Build and maintain BI dashboards, customer health metrics, churn-risk reporting, and predictive models. Partner with Client Success, Product, Sales, and Operations to translate complex findings into actionable recommendations. The role also owns data quality, governance, reporting automation, workflow improvements, and stakeholder communication.

Architects, develops, deploys, and optimizes enterprise-scale data platforms, schemas, pipelines, data models, and integrations. Leads SQL engineering, ETL/ELT frameworks, API ingestion, cloud-native solutions, database performance tuning, analytics, business intelligence, and data governance. Supports Power BI and other BI tools while providing technical leadership across data engineering initiatives. Knowledge of disputes, chargebacks, fraud operations, and case-management systems is preferred.

Design and scale batch and streaming data pipelines, ETL/ELT workflows, data models, warehouses, quality frameworks, dashboards, and AI/ML feature pipelines. Automate reporting and analytics while collaborating with product, engineering, and operations teams. The role also includes internal consulting practice participation, thought leadership, client case studies, and contribution to digital transformation initiatives.

Leads enterprise data engineering and platform execution, including modernization roadmaps, cloud transformation, governance, reliability, operational excellence, budgets, vendors, and investment prioritization. Directs multiple engineering managers and teams across platform engineering, data engineering, integration, and operations. Partners with architecture, security, compliance, analytics, clinical, product, finance, and business leaders to deliver secure, scalable, resilient data capabilities supporting AI, interoperability, reporting, and digital transformation.

Administers Informix, MySQL, and other databases across cloud and hybrid environments. Responsibilities include configuration, maintenance, performance tuning, security remediation, replication, monitoring, Tier 3 support, schema changes, migrations, SQL data extraction, backup recovery testing, automation, compliance, and collaboration with engineering, architecture, security, and application teams.

Build and operate scalable cloud data pipelines, warehouses, transformation layers, and ML production systems. Lead data infrastructure architecture, warehouse performance optimization, DataOps monitoring, CI/CD improvements, data quality testing, and large-scale data product delivery. Collaborate across teams, promote data stewardship, and support batch and streaming pipelines while deploying, serving, and monitoring machine learning models.