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Data Analytics Technology Project Manager Jobs

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Operations Servicing Apps Dev Programmer Analyst
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India , Chennai
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Citi
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Category Manager
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United States , Easton
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Victaulic
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Rn value analysis
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United States , Tucson
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Tucson Medical Center
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Senior Cloud Engineer
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United States , Wilton
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ASML
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Summer Internship - Digitalization
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Norway , Stord
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Aker Solutions
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Infosec Advisor
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Spain , Barcelona
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Spain , Barcelona
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Field Engineer II
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United States , Sacramento
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MobileNet Services
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Strategy Analyst
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Spain , Madrid
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InStaff
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Senior Software Engineer | Computer Vision & Machine Learning
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Germany; Spain , Mannheim; Valencia
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HUBBLR GmbH
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Lead Infrastructure and Automation Engineer
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United Kingdom , London
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Community Fibre
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IT Intern
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United States
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Brkthru
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Engineer Sr Analyst
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India , Chennai; Pune
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Portugal , Lisbon
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India , Pune
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Consultant Specialist
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China , Guangzhou
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Robert Half
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OneStream Developer - C11
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India , Bengaluru
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Sr. Manager of FP&A
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United States , Atlanta
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Explore the dynamic world of Data Analytics Technology Project Manager jobs, a career at the exciting intersection of data science, technology, and strategic business leadership. These professionals are the vital link between raw data potential and realized business value, orchestrating the entire lifecycle of projects that turn complex data into actionable insights and powerful digital solutions. If you are a leader who thrives on building order from complexity and possesses a rare blend of technical acumen and business savvy, this could be your ideal career path. In this role, individuals are primarily responsible for the end-to-end management of technology initiatives centered on data analytics. This involves planning, initiating, executing, and closing projects that may include building new data pipelines, implementing business intelligence platforms, developing machine learning models, or creating sophisticated data visualization dashboards. A typical day involves defining project scope, allocating resources, managing budgets, and meticulously tracking progress against key milestones. They are the central point of communication, translating technical challenges for business stakeholders and conveying business objectives to technical teams with equal clarity. Common responsibilities for professionals in these jobs include leading cross-functional teams of data scientists, data engineers, BI analysts, and software developers. They are tasked with identifying and mitigating risks, proactively solving bottlenecks, and ensuring that projects are delivered on time, within scope, and to the required quality standards. A significant part of their role is to manage dependencies across multiple teams or concurrent projects, often utilizing agile or hybrid methodologies to maintain momentum. They also own the project roadmap, communicating status, issues, and successes to senior leadership to ensure organizational alignment. The typical skill set required for Data Analytics Technology Project Manager jobs is comprehensive. A strong foundation in project management principles, often certified by a PMP or similar credential, is essential. Crucially, they must possess a deep understanding of data analytics concepts, technologies, and the software development lifecycle. This includes familiarity with data warehousing (like SQL, Snowflake), data processing frameworks (like Spark), visualization tools (like Tableau or Power BI), and cloud platforms (like AWS, Azure, or GCP). Beyond technical know-how, exceptional soft skills are non-negotiable: stellar communication, influential leadership, expert negotiation, and sophisticated problem-solving abilities are the hallmarks of a successful manager. Most positions require a bachelor’s degree in a related field like computer science, information systems, or business, with many professionals holding a master’s degree and boasting several years of progressive experience in both hands-on technology roles and project leadership. For those seeking a challenging and high-impact career, Data Analytics Technology Project Manager jobs offer a unique opportunity to shape the data-driven future of modern enterprises.

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