Top Hybrid Data Engineer Jobs in Chicago, IL
The Machine Learning Engineering Specialist at ZS will design and implement ML features, collaborate with client teams, write production-ready code, ensure deliverable quality, conduct testing, participate in agile ceremonies, evaluate new technologies, and support project architecture.
As a Machine Learning Engineer at ZS, you'll build and monitor model pipelines, scale algorithms for large datasets, implement ML Ops, write production-ready code, and collaborate with teams to deliver AI-enabled solutions in healthcare. You'll also research new technologies and contribute to the enhancement of ML engineering platforms.
The Principal Data Management role involves designing and implementing a long-term enterprise data management and governance program. Responsibilities include developing data quality applications, managing relationships with federated data governance groups, and partnering with external vendors to enhance the program's maturity.
The Data Engineer is responsible for designing, developing, testing, and maintaining complex data solutions. They manage risks, lead code reviews, develop data integration solutions, and participate in agile ceremonies, while mentoring peers and influencing technical decisions across teams.
The AI Data Engineer will lead the development of datasets for AI training and testing, collaborating with engineering and product teams to define data specifications, optimize processes, and automate the data lifecycle. Responsibilities include managing data annotation quality, gathering various types of data, and improving efficiency in data handling.
Develop and implement custom GenAI models for various supply chain challenges, manage large datasets, train and evaluate models, deploy models into existing systems, collaborate with cross-functional teams, stay updated on GenAI technologies, and contribute to research and development.
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As a Lead Data Engineer at Capital One, you'll collaborate with Agile teams to design and implement cloud-based solutions. You will work with machine learning, distributed microservices, and full-stack systems, while mentoring fellow engineers and driving technology transformations.
The ServiceNow Data Architect is responsible for establishing data architecture standards, ensuring the quality and usability of the ITSM CMDB, defining the Common Services Data Model standard, and managing configuration management policies and processes. This role involves collaboration with stakeholders to align product demand with data requirements and maintaining the CMDB maturity roadmap.
The Senior Data Engineer/Manager will lead the data strategy for Plasma-Derived Therapies, developing data models and ingestion pipelines while ensuring data quality for real-time decision making. Responsibilities include creating and maintaining data systems, collaborating with IT and business teams, and facilitating data-driven decision-making across the organization.
The Sr. Data Operations Engineer at Beyond Finance will support the data engineering and business intelligence teams, focusing on data sharing, improving SQL queries, assessing database performance, responding to support queries, developing ETL code, and maintaining data security. Key responsibilities include troubleshooting, managing data flow, and collaborating with various stakeholders.
As the Principal for Alternative Data Products, you will drive the strategy and development of products leveraging alternative data. This involves integrating diverse data sources, collaborating with regional teams to meet market needs, and leading efforts to scale these products globally while ensuring compliance with regulations.
The Sr. Data Engineer is responsible for designing and maintaining data architecture and pipelines, solving complex data problems to deliver insights, and creating data products for various teams. The role involves mentoring other professionals, evaluating emerging tools, and ensuring operational efficiency within data solutions while collaborating with multiple engineering teams.
The Associate Principal, Data Analytics Engineering will lead efforts to enhance OCC's analytics capabilities by managing internal corporate data and its accessibility for analysts. Responsibilities include designing and building an analytics data warehouse, automating data processes, integrating data from various sources, ensuring data quality, and creating data visualizations. The role requires collaboration with business and technical teams to enable data-driven decision-making and promote data literacy. The ideal candidate should have strong communication skills and a commitment to continuous learning in data analytics best practices.
Top hybrid Companies in Chicago, IL Hiring Data + Analytics Roles
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