Top Data & Analytics Jobs in San Diego, CA

Teaches undergraduate and graduate Business Analytics courses in a blended format. Responsibilities include developing syllabi and lesson plans, preparing and updating course materials, facilitating online and face-to-face learning, communicating expectations, creating and grading assessments, providing timely feedback, and integrating responsible AI practices into instruction. Faculty must complete ongoing training and professional development while supporting student learning in accordance with university requirements.

Conducts employee climate and customer brand surveys using qualitative and quantitative research methods. Programs surveys in SurveyMonkey, manages survey distribution and response collection, analyzes findings, and develops actionable recommendations to improve employee satisfaction, customer experience, brand consistency, retention, and operational execution.

Performs recurring quality checks on commercial life sciences datasets, investigates anomalies, validates Databricks data ingestion and integrations, maintains data governance documentation, collaborates with vendors and stakeholders, and improves quality processes through SQL, automation, and observability tools.

Own Marvell’s market intelligence modeling, including TAM/SAM/SOM sizing, demand forecasts, scenarios, sensitivity analyses, and emerging-market assessments. Build reproducible analytical pipelines using statistical modeling, machine learning, Python, SQL, and Excel. Govern internal and external market data, develop living dashboards, and translate complex findings into recommendations for executives, Finance, Sales, Investor Relations, business units, and board-level stakeholders.

Designs, builds, and operates large-scale Hadoop-based data pipelines and analytics platforms. Responsibilities include ingesting, transforming, and analyzing structured and unstructured data; developing Spark and streaming workloads; managing distributed systems, databases, and workflow orchestration; troubleshooting production platforms; and delivering reliable, performant, cost-effective data infrastructure for analytics, machine learning, and reporting.

Supports gas compressor engineering and operations through portfolio data governance, financial and resource analysis, forecasting, dashboards, reporting, and decision support. Maintains Planview data, develops Power BI and related analytical tools, improves processes through automation and AI-enabled solutions, and communicates actionable insights to engineering, finance, operations, and leadership stakeholders.

Lead a team of data engineers responsible for building and operating reliable, scalable data pipelines and platform components. Own delivery, production operations, engineering standards, cost and performance optimization, technical debt, and regulatory compliance. Partner with product and data modeling leaders to deliver a governed data platform. Hire, coach, and develop engineers while ensuring strong practices in testing, monitoring, incident response, CI/CD, documentation, and secure infrastructure management.

Develops and maintains Power BI dashboards, semantic models, ETL processes, APIs, and SQL Server data solutions. Integrates data from databases, files, APIs, and enterprise systems; performs data transformation, validation, optimization, troubleshooting, and production support. Participates in DevOps, CI/CD, testing, documentation, and release management while translating stakeholder needs into scalable technical solutions.

Leads customer data architecture for Salesforce Data 360 and Marketing Cloud programs. Defines ingestion, data models, identity resolution, household and vehicle relationships, audience eligibility, consent, data quality, activation, governance, and measurement foundations. Partners with client data, privacy, security, marketing, and Salesforce teams while coordinating third-party data providers and maintaining technical documentation.

Supports enterprise automation initiatives by collecting, cleaning, and analyzing datasets; reviewing reports for accuracy; identifying anomalies, trends, and process improvements; collaborating with Operations, Compliance, Marketing, and Finance teams; exploring development tools; and assisting with reporting, modeling, and analysis solutions during a 12-week internship.