Top Data Engineer Jobs in Salt Lake City, UT
The Data Engineer will design, build, and maintain data pipelines and architectures in AWS, focusing on data integrity and automated testing. Responsibilities include developing ETL processes, standardizing and cleansing data, building data consumption patterns, and implementing automated CICD practices. Documentation and monitoring of data processes are also key aspects of the role.
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.
As a Mandarin Chinese Image Data Contributor, you will locate and upload images matching predefined categories, create questions or prompts for each image, and ensure the relevance and accuracy of content. This role involves working independently to enhance multilingual image interpretation for a Large Language Model.
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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.
As a Senior Data Engineer at Flex, you will design and maintain high-quality data infrastructure services, create scalable data pipelines, manage a secure data warehouse, and collaborate closely with the Analytics team. Your role will involve enhancing data operations and supporting financial products with modern data solutions.
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 Senior Data Engineer at Mozilla, you will focus on the Analytics Engineering team, designing scalable data models and ETL pipelines, enhancing the data platform, and ensuring data governance and compliance. You'll collaborate with data scientists and engineers to facilitate data-driven decisions and optimize data processes.
As a Senior Data Engineer at Mozilla, you will focus on the Analytics Engineering team, designing and maintaining scalable data models and ETL pipelines, improving data infrastructure, and ensuring data quality and compliance. You'll collaborate with data scientists and other engineers to support data-driven decisions and improve access to data across the organization.
As a Senior Machine Learning Engineer for Mozilla's 0din program, you will conduct research, develop security tools for LLMs, engage with researchers, and present findings effectively. Your work will play a role in ensuring the safety of AI technologies by identifying vulnerabilities and collaborating with the community.
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.
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