Top Information Technology Data Engineering Jobs in Austin, TX

The role involves developing Anaplan models, partnering with sales and finance leaders, managing platform administration, and ensuring data integration and documentation.

As a Lead Data Engineer, you will design scalable data platforms, optimizing pipelines, defining data models, and guiding data integration while collaborating with cross-functional stakeholders to align strategies with business goals.

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 design and build of a scalable, secure cross-cloud data platform and marts. Drive selection and optimization of the modern data stack, enforce governance and lineage, and establish reusable data models and best practices to support analytics, BI, and ML use cases across product and engineering teams.

As a Snowflake Data Architect, you will provide ETL support and specialize in Snowflake management, ensuring performance, governance, and optimization of data infrastructures.

As a Data Architect at RapidScale, you'll lead data platform engagements, ensuring delivery quality, managing teams, and designing cloud architectures while supporting ML implementations and client interactions.

As a Staff Data Engineer, lead the technical roadmap for data infrastructure, manage complex data architectures, and mentor engineers while driving the organization's data platform innovations.

The Analytics Engineer will develop the Analytics layer in the data warehouse using dbt, define business logic with SQL, and collaborate with teams to meet data needs.

The Senior Data Engineer develops and maintains data pipelines, evaluates business requirements, integrates data, ensures quality, and collaborates with teams to fulfill data infrastructure needs.

Lead the development and implementation of automation techniques using AI and machine learning to improve life underwriting operations and processes.