Top Remote Data Engineer Jobs in Austin, TX

The Data Engineer will design, build, and maintain analytics-ready Data Marts, create resilient data pipelines, and ensure data integrity, working closely with analytics teams to deliver reliable datasets.

The Data Engineer supports supply chain outcomes by building and maintaining data pipelines, designing data transformations, and collaborating with stakeholders to improve order-to-cash processes.

The Data Engineer I is responsible for building reliable ELT/ETL pipelines, implementing data quality checks, and optimizing data models using dbt, while collaborating with stakeholders to ensure data reliability and consistency.

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.

Lead design and implementation of shared, reusable analytics data models and pipelines. Drive standardization, governance, observability, and CI/CD for analytics; partner with Data Science, Infrastructure, and Product to certify metrics, modernize orchestration, and integrate AI-native tooling.

The role involves writing and deploying scripts for data collection, transforming data sets, diagnosing bugs, and collaborating with other engineers using agile principles.

The Principal Data Engineer will lead the Data Resolution team, focusing on complex data challenges using Spark, system architecture, and mentorship, to optimize graph data pipelines.

As a Data Engineer, you will build and optimize data pipelines, ensuring accurate data delivery that informs pricing and market analytics at Alt.

The Data Engineer will build and maintain data pipelines, optimize queries, collaborate with teams, and ensure data quality across Google Cloud systems.

The Data Engineer will design and maintain data models on Snowflake, enforce data standards, manage security, optimize SQL, implement CI/CD, and mentor junior staff.

The job involves leveraging AWS and Snowflake for data engineering tasks within a technology-focused company, requiring US residency.

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

The Lead Data Consultant will design and deliver scalable data solutions, manage project teams, and optimize client data environments, ensuring effective project execution and communication.

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.

The Data Engineer will build and maintain data infrastructure, design data pipelines, and develop reusable frameworks, leveraging technologies like Azure Databricks and PySpark for data processing and transformation.

The Data Engineer will enhance the Enterprise Data Warehouse, modernizing ETL processes, optimizing data transformations, ensuring data quality, and providing production support while collaborating with cross-functional teams.

Design, build, and operate Spark-based ETL pipelines on AWS. Collaborate with stakeholders to deliver reliable data products, ensure data quality and governance, optimize performance, and maintain operational excellence of the data platform.

Design, build, and optimize distributed query solutions using Starburst/Trino. Enable secure, governed data access across cloud and on-premises sources, implement data federation and query optimization, support IAM and governance in a federal environment, develop backend services and CI/CD, and troubleshoot performance in cloud-native systems.

Design, build, monitor, and optimize large-scale ETL/ELT data pipelines and data architecture. Integrate data sources, support analysts and data scientists, automate processes, ensure reliable data delivery, and write maintainable code.

The Data Engineer will manage data extraction pipelines, modernize data systems, implement monitoring tools, optimize workflows, and support compliance requirements using various tools and platforms.

As a Data Engineer, you will build and optimize data pipelines, manage ETL workflows, and ensure efficient data access and quality within the infrastructure.

The Data Migration Engineer will design and execute SQL-based ETL processes for migrating public safety data, ensuring high-quality data integration and collaboration with internal and external teams.

Implement client revenue cycle data into company systems by creating and configuring ETL processes, building data transformations and logical/physical schemas, documenting solutions in Jira, attending client meetings, and mentoring team members to ensure post-implementation data integrity.

The role involves building and optimizing data pipelines, modeling datasets, applying machine learning techniques, and supporting data strategies. Candidates should have experience with Python, data lakes, warehousing, and related technologies.

Build and operate scalable data pipelines and analytics-ready datasets using Python, dbt, and BigQuery. Develop Looker dashboards, ensure data quality and observability, optimize performance and cost, integrate data workflows with backend services and CI/CD, and support analytics, experimentation, and production use cases.