Top Remote Data Engineer Jobs in San Diego, CA
Lead the development of AI and Machine Learning solutions to enhance user experience and workflow efficiency for enterprise services at ServiceNow. Collaborate with a team of scientists, developers, and product managers to deliver innovative solutions to enterprise customers worldwide.
The Machine Learning Quality Engineer at ServiceNow will be responsible for testing AI/ML models, designing testing strategies, creating comprehensive test plans, and collaborating with developers to ensure high-quality results. The ideal candidate should have a Bachelor's or Master's degree in Computer Science/Engineering, 3 years of work experience, strong test automation skills in Java/Python, and experience with automated testing frameworks and agile methodology.
Join Paper, an educational support system company, as a Senior Data Engineer. Help optimize products by building a learning profile for each student using collected data. Work on personalized tutoring, practice centers, and college readiness solutions. Must have 5 years of experience in Python, SQL, AWS, data engineering, and ETL processes.
The Senior Data Integration Consultant interfaces with customers' functional teams to understand the data and automation needs required to achieve a connected reporting experience. They will translate functional needs into technical requirements and work closely with customers’ technical teams to connect the Workiva platform to the customers’ enterprise systems. This role is responsible for the design and delivery of the Data Management Suite comprised of Wdata Tables/Queries/Views, Chains, and Data Prep.
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Design and develop data models in Snowflake with DBT for internal business partners. Write advanced SQL queries for ELT and data warehousing. Collaborate with team members on projects and promote business data models for self-service reporting. Follow data governance best practices and standards. Utilize tools like Snowflake, DBT, SQL, Python, and more for ETL, data modeling, and analytics.
The Staff Analytics Data Engineer will lead and own strategic data projects, architect scalable data pipelines, solve complex data challenges, refine development processes, and collaborate with business partners. The role involves developing and optimizing data pipelines for actionable insights and ML workloads across Pfizer's Commercial business.
Senior ML Engineer role at Grammarly's On-Device ML team responsible for proposing, designing, and implementing strategic new features using ML models to enhance writing assistance capabilities. Collaborate with core product teams, monitor deployment, and leverage academic research to advance technology.
As a Machine Learning Engineer at Liftoff, you will own ML models with direct business impact, adopt new technologies, mentor team members, monitor ML research, and influence team roadmaps. Requires 8+ years of ML experience, strong engineering skills, and a degree in Machine Learning, Math, Physics or similar. Experience with AdTech is a plus.
Design, develop, and maintain scalable solutions for ongoing metrics, reports, and analyses to support analytical and business needs. Translate business problem statements into analysis requirements and collaborate with the team to measure customer experience. Develop queries, visualizations, troubleshoot data-quality issues, and recommend improvements to back-end data sources.
The Staff Machine Learning Engineer role at Cruise involves driving applied ML research and development for urban roads related to Perception and Object Tracking. Responsibilities include exploring new algorithms, optimizing on-road performance, guiding technology choices, and enabling team members. Required qualifications include a PhD/MS degree in computer vision or machine learning, experience in deep learning projects, programming skills in Python and/or C++, expertise in ML frameworks, strong communication skills, and the ability to design scalable architectures.
Ontra is seeking a Senior Data Engineer to create and own a data engineering roadmap, collaborate with product and engineering teams, and build data processing pipelines and infrastructure. The role requires 5+ years of core data engineering experience with technical skills in SQL, Python, Snowflake, dbt, Airflow, Kubernetes, Docker, DataDog, and AWS.
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