Top Data & Analytics Jobs in Austin, TX

Build and maintain scalable GTM data pipelines, marts, semantic models, and dashboards supporting headcount planning, quota attainment, pipeline, and sales effectiveness. Partner with GTM analysts and stakeholders to establish reliable metrics, enable data tools, document systems, and develop AI-powered natural-language data querying capabilities. Translate complex data concepts for executives and engineers while ensuring high-quality, maintainable data products.

Develop dashboards, data pipelines, forecasts, and scenario models for engineering leadership. Analyze resource utilization, headcount, budgets, and operational performance while applying AI/ML, LLMs, and automation to improve reporting and workflows. Translate complex, inconsistent data into actionable recommendations and identify process improvements across engineering operations.

Designs and maintains scalable data infrastructure, ETL/ELT pipelines, canonical datasets, and AI context layers. The role improves data quality and alignment across sales and finance systems, investigates data inconsistencies, leads requirements through UAT and implementation, supports analytics self-service, and partners with cross-functional teams to deliver process improvements and reliable business data.

Leads Expedia Group’s data engineering, software engineering, AI, and innovation capabilities for Marketing Automation and MarTech. Sets enterprise technology strategy, oversees scalable data platforms, pipelines, APIs, integrations, governance, security, observability, and responsible AI foundations. Builds high-performing engineering teams, manages modernization and platform investments, enables analytics and experimentation, and partners with senior stakeholders to improve customer engagement, operational efficiency, and technology delivery.

Lead the strategy and governance for GTM analytics across pre-sales, post-sales, solutions engineering, forward-deployed engineering, and professional services. Establish trusted source-of-truth metrics, data models, semantic layers, self-service analytics, and AI-assisted querying. Partner with Data, Finance, Sales, and Services leaders to resolve metric definitions, improve data access, consolidate reporting, and guide cross-functional programs without direct authority.

Own the technical strategy, architecture, and roadmap for enterprise clickstream data collection across web and mobile products. Define event taxonomies, instrumentation specifications, data contracts, and measurement standards; validate data quality using SQL and Snowflake; investigate tracking discrepancies; and drive architectural improvements. The role partners across engineering, product, marketing, analytics, and QA, while mentoring technical teams and promoting governed, self-service analytics.

Build and own end-to-end data products, including pipelines, transformations, semantic models, dashboards, metrics, and AI-enabled workflows. Partner with business and technical stakeholders to turn ambiguous questions into trusted, maintainable solutions. Establish data quality testing, documentation, monitoring, and governance while improving architecture and automation. Use Snowflake, dbt, Power BI, and related technologies to support analytics across Marketing, Product, Finance, and Engineering.

Build and maintain dbt data models, SQL transformations, ingestion pipelines, orchestration, and Tableau dashboards in support of HR and enterprise analytics. Own data quality, metric standardization, privacy controls, Row-Level Security, documentation, CI/CD, and troubleshooting from source systems through reporting. Partner with stakeholders to define requirements and KPIs, support workforce forecasting, optimize BigQuery performance, and pilot AI-assisted analytics using Google Gemini.

Staff Data Engineer leading architecture and technical direction for real-time and batch motorsports data platforms. Responsibilities include telemetry ingestion, streaming systems, data quality, observability, cloud platforms, reliability, incident response, technical standards, roadmap planning, stakeholder influence, and mentoring. The role delivers scalable solutions supporting race-day operations and cross-functional analytical products.

Analyze post-sales customer lifecycle data, including adoption, retention, renewals, churn, and expansion. Build Salesforce reports and dashboards, query and validate data with SQL, and create recurring analyses and visualizations using Excel, Tableau, and other BI tools. Partner with Customer Success, CS Operations, Analytics, BI, and Sales Systems teams to improve reporting, investigate trends, identify risks, and communicate actionable insights to technical and non-technical stakeholders.