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Top Hybrid Data Engineer Jobs
As a Senior Machine Learning Engineer, you will work on productionizing machine learning applications and systems at scale. You'll participate in the design and implementation of ML applications, collaborating with Product and Data Science teams, and focus on optimizing ML models, building data pipelines, and ensuring high performance and availability of solutions. You will leverage cloud technologies and follow best practices in responsible AI.
As a Staff Data Engineer, you will lead the development of data infrastructure for marketing analytics at Square. This role involves building pipelines, translating stakeholder needs into ETL requirements, and analyzing data trends to support business reporting and decision-making.
As a Staff Data Engineer on the Marketing Data Engineering team, you will build and maintain data infrastructure to support revenue growth. You will design and manage data pipelines, collaborate with web analytics and SEO teams, ensure accurate data logging, and assist with data analysis to drive investment decisions and enhance reporting accuracy.
As a Staff Data Engineer on the Marketing Data Engineering team, you will build and maintain foundational data infrastructure essential for driving revenue growth. Your role involves creating data pipelines, collaborating with analytics teams, and ensuring data accuracy for business reporting and decision-making, impacting multiple stakeholders at Square.
Lead the design, development, and deployment of large-scale data systems. Build and maintain data pipelines, ensure data quality, and collaborate with teams for data-driven insights. Optimize ETL processes and troubleshoot data inconsistencies while recommending data integration solutions.
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The Sr Machine Learning Engineer will develop and maintain algorithms for Hulu's recommendation system, using advanced machine learning methods. Responsibilities include feature engineering, optimizing data pipelines, and collaborating with product and data teams to enhance personalization and analysis processes.
The Senior Data Engineer will be responsible for building data integration pipelines for data lakes and warehouses, ensuring data quality and integrity, and collaborating with stakeholders to meet business requirements. The role includes optimizing data transformation processes and promoting coding standards.
The Head of Privacy, Data and AI Governance will lead the strategy and execution of integrated governance for data privacy and AI systems at MassMutual, ensuring compliance and ethical practices. This role includes building a strong team, developing a multi-year strategy, implementing risk management policies, and enhancing governance tools to protect the organization's data and reputation.
As a Senior Data Operations Engineer at Klaviyo, you will develop and maintain the data infrastructure, create data models for business analytics, and collaborate across departments to support decision-making. You will manage cloud-native data environments focused on security and scalability, utilizing a range of technologies to handle large data sets and promote a self-service analytics platform.
As a Data Science Lead in HR Data & Analytics, you will conduct analyses of HR and business data to provide actionable insights. You'll design and implement analytical models, collaborate with users to understand requirements, develop solutions, and guide junior team members. Your role will include ensuring data quality and adhering to compliance policies.
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The role involves developing and optimizing NLP algorithms, training large language models, collaborating with cross-functional teams, and contributing to machine learning research initiatives. The engineer will drive improvements in the data processing pipeline and mentor junior team members.
The Data Engineer will develop and implement data solutions to meet business requirements, create data pipelines, conduct testing, and troubleshoot issues. The role includes working with SQL for data analysis and collaborating with various stakeholders to ensure data infrastructure is effective and meets architectural standards.
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