Top Data Engineer Jobs in Austin, TX

As a Data Engineer at Thatch, you'll develop data infrastructure, build ELT pipelines, and collaborate across teams to provide analytics insights.

The Data Engineer will build scalable privacy-centric data frameworks, engineer data pipelines, and ensure compliance with privacy regulations at Netflix.

The Data Engineer will architect and expand data products for Netflix's Ads business, developing data pipelines, collaborating with analysts, and ensuring data quality.

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.

As a Data Engineer, you will develop and manage the data infrastructure that supports HTS Media's advertising business, build ETL/ELT pipelines, and enable data-driven insights for advertisers and internal analytics.

As a Data Engineer, you'll design, implement, and optimize data solutions from various sources to support business sales and finance teams.

Lead the evolution of SimplePractice's data stack, building scalable systems for analytics, reporting, and product insights in a fast-paced environment.

The Senior Data Engineer will develop and maintain data pipelines, collaborate with Analysts, and ensure high code and data quality on the Hungryroot Analytics model.

Lead design and delivery of data solutions in Adobe Experience Platform, optimize data models, mentor junior engineers, and drive strategy.

The Data Engineer will design, develop, and optimize large scale data pipelines and ensure effective data delivery for cross-functional teams.

As a Data Engineer, you will design data storage systems, build ETL pipelines, optimize data reliability, and collaborate across teams, leveraging modern technologies for data management and processing.

As a Data Engineer, build efficient data processing systems, model data to support analytics, and collaborate with teams to enhance Netflix's data-driven culture.

The Data Engineer will develop cloud-based data tools, construct datasets using SQL, build data pipelines on AWS, collaborate on data solutions, and implement automation for security standards.

The Freelance Data Engineer will analyze data, design databases, manage data operations, and collaborate on data-driven projects to optimize data infrastructure.

Seeking an experienced Data Engineer to design and optimize data infrastructure, build scalable pipelines, and ensure data quality and governance.

Design and develop data solutions, optimize ETL/ELT pipelines, integrate ML models, collaborate with engineers, and operationalize analytics for semiconductor R&D and operations.

Design and maintain scalable data pipelines, collaborate with cross-functional teams, manage data architectures, optimize Snowflake performance, and enhance data workflows.

Design, develop, and manage data infrastructure for internal and client projects, focusing on large-scale data pipelines, APIs, and cloud deployments.

Design and optimize data pipelines, work with structured/unstructured data, ensure data quality for analytics, and collaborate with data scientists.

The Staff Data Engineer will architect and operate the Databricks lakehouse, managing data ingestion, governance, and analytics collaboration with cross-functional teams.

The Data Services Integration Engineer automates data workflows, integrates systems using Microsoft Power Platform, and ensures data integrity through governance policies and documentation.

You will design and build data-driven Streamlit apps, automate analytics pipelines, and monitor application performance while collaborating with platform engineers.

Analyze and develop data solutions, lead projects, translate business requirements, provide support for ETL processes, and mentor junior team members.

Design, build, and maintain scalable data infrastructure in the cloud using AWS services and Infrastructure as Code to ensure data reliability and performance.

The intern will assist the Data Operations team in optimizing data workflows, developing automation scripts, and maintaining data systems while gaining hands-on experience.