Top Remote Data Engineer Jobs in Austin, TX
This role involves leading a team of Data and Software Engineers responsible for ingesting and processing critical loan data from multiple partners. The manager will mentor and train team members, participate in code reviews, manage large-scale projects, and collaborate with project management to improve engineering processes.
As a Lead Data Engineer, you will design, develop, and implement data pipelines, warehouses, and lakes while ensuring data quality and accuracy. You will lead strategic discussions, document requirements, and develop scalable data solutions. Additionally, you will maintain data infrastructure and stay updated on emerging technologies.
The Principal Data Engineer will design, develop, and maintain ETL pipelines for data acquisition and transformation. Responsibilities include collaborating with teams to understand data needs, utilizing AWS Glue, optimizing ETL processes, and applying data governance practices. The role requires strong technical skills in Python, Spark, and SQL, along with experience in data matching and analytics.
The LLM Data Engineer will design, implement, and maintain data pipelines for Generative AI platforms, focusing on techniques like Supervised Fine Tuning and Reinforcement Learning from Human Feedback. Responsibilities include data source integration, optimizing workflows, managing various vector store technologies, and collaborating with teams to ensure data quality for AI/ML models.
As an Analytics Engineering lead within the Ads Data Science team at Reddit, you will develop robust data pipelines and user-friendly tools, ensuring data quality and reliability for effective data analysis. You'll mentor data analysts and collaborate with different teams to foster a data-driven culture focusing on automation and self-service data access.
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The Data Engineer III is responsible for architecting and maintaining scalable tooling and infrastructure for data management, including building automated data pipelines and managing data storage. The role involves collaborating with Data Scientists for model improvements and ensuring data quality and availability, while also coaching teams on data-driven decision making.
The Senior Data Engineer is responsible for analyzing existing data sets, defining data requirements, and performing statistical modeling to improve decision-making processes. Key responsibilities include managing projects, coaching lower-level professionals, developing reports using SQL, and delivering analytic solutions while ensuring data quality and compliance with development standards.
As a Data Engineer at Demyst, you will build data-driven solutions for financial institutions, leveraging external data and innovative datasets through the company's proprietary software architecture and cloud infrastructure. Responsibilities include data analysis, ETL, API development, and collaborating with stakeholders to deliver insights that meet business objectives.
As an Analytics Engineer, you will create and optimize data models, work with product and engineering teams to ensure accurate data generation, collaborate with stakeholders on project timelines, and improve data processes using various analytics tools.
As a Principal Data Engineer, you will lead data engineering initiatives, architect integrated data platforms, maintain ETL pipelines, and utilize AWS services. Collaborating with various teams, you will ensure data efficiency and regulatory compliance while mentoring fellow engineers and optimizing data processes using advanced statistical methods and technologies like Docker, Snowflake, and Spark.
Top remote Companies in Austin, TX Hiring Data + Analytics Roles
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