Top Senior Level Data Engineer Jobs in Austin, TX

As a Data Engineer, you will be responsible for designing and implementing data infrastructure, building data pipelines, ensuring data quality and integrity, and collaborating with cross-functional teams to optimize data delivery.

Building and maintaining production data pipelines for analytics, developing tooling and solutions for data practitioners, improving observability and maintainability in the data environment, creating and implementing standards for data flows, and automating processes throughout the data environment.

Lead the design and development of migrating on-prem vehicle data systems to cloud environments. Design data solutions with a focus on security, privacy, and scalability. Train and mentor staff engineers in cloud development principles. Influence technology strategy and adoption decisions.

Seeking a Staff Machine Learning Engineer - MLOps Platform to design data pipelines and engineering infrastructure, evaluate new technologies, build CI/CD pipelines, support model development, and collaborate with product and engineering teams. Requires advanced degree or relevant experience in computer science or related fields, proficiency in Python, R, Spark, SQL, AWS, and MLOps frameworks.

Restaurant365 is looking for a Sr Data Engineer to join our data warehouse team as a technical leader that enables the flow of information and analytics across the company. The Sr Data Engineer will lead the execution of the enterprise data lake, data warehouse, and analytic solutions.

Senior Software Engineer in the Central AI team at Atlassian, responsible for building and maintaining core infrastructure for machine learning models and pipelines. Leading projects from design to launch, collaborating with internal teams, and setting expectations. Offering competitive compensation and benefits. Requires 5+ years of experience, fluency in Java/Kotlin and Python, experience in Continuous Delivery, Continuous Integration, and large-scale distributed systems using AWS and Apache Spark.

Design and build data pipelines, document database designs, monitor and optimize production systems, perform code reviews, and work with cloud technologies and databases.