Top Hybrid Data & Analytics Jobs

Responsible for transforming sales data into strategic narratives, providing insights for executive decision-making, and leading a team of analysts.

Serve as a strategic analytics partner across Product, Growth, Engineering, Design, and Leadership. Define KPIs, measurement frameworks, experimentation strategies, and A/B tests; build executive dashboards and scalable dbt datasets; deliver product and marketplace insights; manage technology-category and vendor data; research cybersecurity and AI markets; and use LLMs to improve workflows and enrich the product database.

Leads complex data extraction and transformation workflows across large, heterogeneous datasets and non-standard formats. Assesses source systems, develops defensible extraction strategies, troubleshoots difficult data conditions, and creates reusable methods, quality controls, and documentation. Partners with eDiscovery, analytics, forensics, and client-facing teams, while scoping technical work, identifying risks, supporting pricing, escalating issues, and guiding junior staff.

Leads Pebl’s data strategy, modern data infrastructure, security, governance, analytics, and AI integration. The Director of Data will architect scalable pipelines, turn data into business insights, embed AI across products and internal workflows, communicate findings to executives, and build a high-performing team of data engineers, analysts, and AI specialists. The role requires close collaboration with Marketing, Sales, Operations, Finance, Legal, and R&D, with in-office work in Palo Alto Monday through Wednesday.

Leads the architecture, development, and delivery of enterprise data platforms using Snowflake, AWS, Python, Spark, Informatica, and modern ELT frameworks. Designs Data Vault and dimensional models, scalable ingestion pipelines, and cloud data architectures. Provides technical leadership, mentors engineers, manages delivery across initiatives, and ensures data quality, performance, governance, monitoring, and production reliability. Partners with business and technical stakeholders to translate requirements into robust data solutions.

Remote research internship supporting semiconductor and AI industry analysis: data collection, market research, basic financial modeling, preparing reports and presentations, attending team meetings, and developing research skills with mentorship and feedback.

Analyzes unstructured customer feedback using text analytics, NLP, LLMs, SQL, Python/R, and BigQuery to identify sentiment, root causes, trends, and customer experience opportunities. Owns feedback taxonomies, models, workflows, and validation standards; connects feedback with behavioral and operational data; delivers business recommendations and executive storytelling; partners cross-functionally on measurement strategy and roadmaps; and mentors junior analysts.

Business Analyst partners with stakeholders and developers to analyze requirements, improve business processes, and implement IT system solutions. Responsibilities include functional documentation, data flows, end-to-end testing, User Acceptance Testing, application support, access issue resolution, reporting and visualizations, user training, and project participation. The role requires SDLC experience, business analysis or software implementation experience, strong communication, project management, and familiarity with Agile and waterfall methodologies.

Build trusted analytics models, reports, dashboards, and light predictive analyses for revenue, finance, procurement, operations, and renewable energy stakeholders. Develop dbt models in Snowflake, analyze SAP data, maintain curtailment reporting, automate workflows with Python, validate data quality, and document metrics and data assets. Partner with business stakeholders to gather requirements, prioritize requests, and communicate insights. This hybrid role requires working in the Scottsdale office three days per week.

Owns executive reporting for autonomous vehicle system performance, including the weekly Software Performance Review and broader commercial readiness analyses. Synthesizes robotics data, diagnostic evaluations, and performance metrics into strategic narratives for senior leadership. The role aligns cross-functional engineering data, automates reporting pipelines and presentation generation, establishes visualization standards, and mentors junior engineers. It requires deep knowledge of robotics, autonomous vehicle performance, data architectures, executive communication, and AI-assisted development workflows.