Top Data & Analytics Jobs in Austin, TX

Maintain and automate marketing performance reporting, build actionable Power BI dashboards, query and integrate data from ad platforms and CRMs, detect anomalies, and provide insights on CTR, CVR, ROAS, attribution, and testing to support paid media and SEO teams.

Design, build, and maintain scalable ETL/ELT pipelines and data warehouse architecture. Partner with cross-functional teams to define KPIs, ensure data quality and governance, own billing data infrastructure, and deliver dashboards and analytics for leadership while mentoring peers.

Design, build, and maintain scalable data pipelines and API integrations; implement data quality monitoring and alerting; troubleshoot data issues; collaborate with business stakeholders; support CI/CD processes and scale architecture for future needs.

Lead analytics for Zynga Poker by running A/B tests, building ETL pipelines and dashboards, analyzing player behavior, tuning game economy, and improving fraud/bad-actor models. Collaborate with product, design, and data science teams, contribute to AI/LLM initiatives, and maintain telemetry and BI tools to inform strategic decisions that impact millions of players.

The Staff Data Engineer will lead design and implementation of analytics platforms and data products, collaborate cross-functionally, mentor engineers, and drive best practices at Upside.

Run and analyze product experiments, define product metrics and telemetry for web and mobile, build funnel/retention/cohort analyses using SQL and Python on Snowflake, maintain Omni dashboards, create AI-agent workflows to automate routine analysis, and translate findings into clear product recommendations alongside PMs, designers, and engineers.

Extract, transform, validate, and load client and Enverus data into MineralSoft using AI-enabled extraction tools and ETL processes. Configure mappings, run queries and reports, troubleshoot integrations with EnergyLink, and ensure data quality and completeness for internal and client use.

Design, build, and operate scalable real-time and batch data pipelines ingesting high-frequency telemetry, simulation, and trackside data. Own Kafka/Flink streaming components, Databricks lakehouse implementations, and infrastructure-as-code deployments. Develop software in Python/Java/SQL, integrate systems, automate testing and releases, performance-tune pipelines, and mentor peers to ensure resilient, secure, high-performance data delivery for motorsports teams.

Design, build, and maintain scalable data pipelines and cloud data infrastructure (warehouse, RBAC, validation). Collaborate with data scientists and engineers, orchestrate ML pipelines, ensure data quality/security, optimize cost and performance, lead incident response and mentor teammates.

Analyze supply chain and supplier performance data, build KPI dashboards and scorecards, support AS9100 documentation, drive process improvements, support supplier escalations and new product launch planning to improve efficiency, scalability, and cost.