Top Remote Data Engineer Jobs in Austin, TX

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.

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

As a Senior Data & Analytics Engineer, you'll lead data initiatives, manage a team, and ensure data quality while turning insights into actionable decisions across the company.

The Senior Data Engineer will design and implement complex data models, collaborate on data governance, lead data initiatives, and mentor team members.

The Senior Data Engineer leads data engineering efforts, coordinating project execution and collaborating with teams to develop data solutions for Navy and DoD programs.

The Senior Data Engineer will manage and transform data pipelines, implement changes in Snowflake, monitor costs, and resolve data issues.

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.

The Data & Analytics Engineer will model and serve data, improve architecture, and collaborate with teams to sustain the data strategy, requiring 5+ years of experience.

Nagarro seeks an Associate Principal Engineer in Big Data to leverage extensive IT experience for strategic organizational value. The role values self-starters and innovation.

As a Lead Data Engineer, you'll optimize data workflows, manage data engineering projects, mentor junior engineers, and ensure robust data solutions meet business needs.

As a Senior Data Engineer, you'll design, build, and optimize data infrastructure while collaborating with teams to enhance data flow and integration across platforms.

The role involves building and optimizing data pipelines, managing data integration, supporting analytics, and collaborating with cross-functional teams to enable data-driven decisions.

Lead the architecture and development of scalable data pipelines, mentor team members, and align data engineering practices with business objectives in a complex technical environment.

The Manager, Data Migration will oversee data collection, migration planning, and work with engineers on data translation and operations, while building a data migration team.

The Senior Data Engineer will design and maintain data pipelines, automate workflows, and create internal data tools to enhance operations and analytics at Mangomint.

The Senior Data Engineer will design and build data pipelines and infrastructure to support data science and business intelligence solutions, utilizing AWS services and streaming technologies.

Design and maintain high-quality data pipelines, develop DBT models, collaborate with analytics and data science teams, and optimize data operations for scalability.

As a Senior Data Engineer, you will enhance the data lakehouse, optimize data workloads, perform complex transformations, and develop frameworks to improve delivery velocity, focusing on cybersecurity solutions.

The Senior Data Engineer will design and build scalable data pipelines and models, ensuring data quality and optimizing data infrastructure using AWS and Snowflake. Responsibilities include leading projects, integrating APIs, and collaborating across teams to enhance data products for value-based care.

As a Senior Data Engineer, you will design and build data products, establish best practices, and lead technical initiatives in data architecture and workflows within the single-family rental industry.

Lead the design of DataOps platforms, focusing on scalable data infrastructures and automation frameworks. Oversee robust data orchestration and establish quality frameworks.

As a Senior Data Engineer, you'll design and implement a Snowflake-centric data architecture, operationalize ML and LLM processes, and enable advanced analytics while collaborating with cross-functional teams.