Top Senior Level Data Engineer Jobs in Rochester, NY
The Cloud Data & Analytics Senior Manager will help organizations leverage data analytics to drive business results. Responsibilities include aligning client data strategies, assisting in platform selection, and migrating to modern cloud environments. The role requires leadership in managing diverse teams, problem-solving, and contributing technical knowledge in cloud data architecture.
As a Senior Manager in Cybersecurity and Forensics, you'll manage complex data protection projects, helping clients with governance strategies, data management, and mitigating information risks. You will lead teams to address stakeholder needs, implement governance controls, and enhance organizational capabilities in navigating legal and regulatory challenges.
As a Solutions Architect Manager, you'll lead teams to help clients implement Oracle's data and analytics solutions, focusing on data strategy, governance, and effective project execution. Responsibilities include coaching team members, analyzing complex data proposals, and developing solutions using multiple sources of information.
The Senior Data Engineer will design, develop, and deploy code for clinical data solutions, manage project timelines, and provide guidance to team members. This role includes configuring and supporting the elluminate platform, ensuring quality control of reports, and collaborating on various data-related tasks.
The Sr. Enablement Technology & Data Consultant leads the management of content management platforms and analytics for Group Benefits, partnering with various departments to improve effectiveness through strategic analysis and recommendations. This role oversees Highspot governance, data visualization, operational reporting, and complex technology initiatives, ensuring accurate decision-making and project completion.
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The Solutions Architect at CDW specializes in Microsoft Data and AI solutions, engaging directly with clients to understand their business needs, creating technical solutions, and overseeing the delivery process. This role emphasizes presales support, document preparation, sales planning, partner relationship management, and the development of intellectual property
As a Principal ML Infrastructure Engineer, you will define and drive the technical vision for Thumbtack's ML infrastructure, lead cross-functional initiatives, architect scalable ML systems, establish engineering standards, mentor teams, and align infrastructure capabilities with business objectives.
As a Senior Machine Learning Engineer at Affirm, you will develop machine learning models for assessing creditworthiness, build training and monitoring systems, and collaborate with product and engineering teams. You'll implement data pipelines and drive innovations in credit decisioning with cutting-edge technologies.
The Senior Data Engineer will design and implement ETL processes in a cloud environment, develop monitoring solutions, document datasets, and collaborate with the Data Science team. This role requires building ETL processes and a strong understanding of data modeling.
As the Director of Data Science & AI, you will lead a team to develop AI and ML solutions that align with the business strategy. Responsibilities include overseeing the ML workflow, collaborating with Product and Engineering, and managing a high-performance team to drive customer-centric analysis and strategic initiatives.
Join the Data Center Selection team to improve the quality and cost of colocation sites while managing vendor relationships and driving best practices. Responsibilities include defining vendor strategies, managing deals end-to-end, and collaborating with internal teams to support infrastructure growth. Strong relationship management and negotiation skills are essential.
As a Principal Full Stack Engineer, you'll lead the design and integration of ad analytics and ad fraud products, manage the software development lifecycle, mentor junior engineers, and ensure best practices in a collaborative environment. You'll work with product teams to gather requirements, build scalable systems, and automate cloud infrastructure.
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