Top eCommerce Data & Analytics Jobs in Austin, TX

Lead a distributed SQL team and own the end-to-end service model for custom analytics: intake, scoping, delivery, QA, documentation, and SLAs. Serve as a customer-facing technical lead, build scalable workflows and request taxonomy, partner cross-functionally, and balance customer delivery with internal platform priorities.

Analyze digital customer journeys and site behavior to identify friction, explain marketing performance, and provide actionable insights. Maintain dashboards, support A/B and multivariate testing, collaborate with developers on tagging and tracking, and drive optimization to improve conversion and retention.

The eCommerce Ads & Performance Analyst manages and optimizes paid advertising campaigns across platforms, analyzes performance metrics, and provides data-driven recommendations for improvements.

Design, build, and maintain scalable ETL/data pipelines across distributed systems. Ensure data quality, integrity, security, and high availability. Monitor and optimize pipeline performance, perform root cause analysis, document systems, collaborate with global teams, and participate in on-call rotations to support production data systems.

Design, build, and maintain scalable data pipelines and tenant-aware APIs to ingest and transform data from varied sources. Work with event-driven and batch architectures, implement authentication and integration patterns, ensure observability/monitoring, optimize data flows for cost and performance, and collaborate with product, infrastructure, and engineering teams to onboard and maintain data sources at scale.

The Data Engineer will develop and maintain data pipelines, perform data extraction and transformation, and support data analytics across the enterprise.

Early member of the Data & Analytics team responsible for end-to-end analyses and data products. Build and maintain dbt models, semantic layers, and dashboards (Power BI). Partner with Finance, Merchandising, Marketing, Operations and others; own metric definitions, validate AI-generated SQL/dbt/Python, investigate data discrepancies, and help evolve Snowflake-based data infrastructure and governance.

The Lead Risk Analytics Data Scientist will develop risk pricing, design data models, automate workflows, and communicate insights to leadership. Responsibilities include owning the risk narrative, building analytics foundations, and utilizing AI to enhance efficiency.

The Data Solutions Architect at MANSCAPED will manage the enterprise data architecture, ensure security and scalability, and support BI reporting and advanced analytics.

As a Senior Analytics Engineer, you will design the financial data backbone, integrating ERP data, building profitability models, and enabling data-driven planning in collaboration with Finance and Operations.