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Manager Data & Analytics Jobs

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Supply Planning Lead
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United Kingdom
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Octopus Energy
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Cybersecurity Specialist
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Italy , Cadoneghe, Padova
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UNOX
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Head of Sixth Form
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Egypt , Cairo
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International School of Bergamo
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Senior Automation Engineer
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United States , San Diego
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Robert Half
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Senior Account Executive
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Canada , Vancouver
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100000.00 - 130000.00 USD / Year
VoPay
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Java API Engineer
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India , Pune
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Barclays
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Systems Integration and Test Engineer
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United States , San Mateo, California
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127500.00 - 212500.00 USD / Year
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Skydio
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Facilities Coordinator
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Blackrock Health Hermitage Clinic
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Quality Assurance Analyst
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United States , Philadelphia
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Robert Half
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Sales Operations Analyst
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United States , Philadelphia; Englewood; Miramar; Southfield; New York
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59775.91 - 107596.64 USD / Year
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Comcast Advertising
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Performance Marketing Manager
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United States , San Francisco
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123900.00 - 148028.00 USD / Year
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Intercom
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Technology Risk Governance Manager
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Australia , Richmond
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Australia Post
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Full Stack Engineer
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Andersen
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Architect - Healthcare IT Solutions
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Canada
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107770.00 - 127000.50 CAD / Year
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Altera Digital Health Inc. UK
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Legal Counsel
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Canada , Toronto
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137000.00 - 153000.00 CAD / Year
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PointClickCare
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Logistics and Sustainment Analyst
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United States , San Diego
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55000.00 - 75000.00 USD / Year
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KAIROS Inc
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Senior AI Engineer
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France , Toulouse; Paris
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efficy
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Digital Programs Marketing Specialist
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Portugal , Lisbon
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PagerDuty
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Software Engineer
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India , Bangalore
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Hewlett Packard Enterprise
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Intern, Digital Consulting, MDS, Malaysia
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Malaysia , Kuala Lumpur
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Marriott Bonvoy
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Explore the pivotal world of Manager Data & Analytics jobs, where strategic leadership meets the power of information. Professionals in this high-impact role sit at the crossroads of business strategy, technology, and data science, acting as the key translators who turn raw data into actionable intelligence and competitive advantage. A Manager of Data & Analytics is fundamentally responsible for building, leading, and scaling an organization's data capabilities. This involves overseeing teams of data analysts, scientists, and engineers to ensure that data infrastructure, governance, and analytical outputs directly support and drive business objectives. The common responsibilities in these leadership positions are multifaceted. Typically, managers in this field own the end-to-end data pipeline, from governance and quality assurance to advanced analysis and insight delivery. They define the data strategy, select and manage technology stacks (including cloud platforms, data warehouses, BI tools like Tableau or Power BI, and increasingly, AI/ML frameworks), and establish robust data governance policies. A core duty is to partner with executive leadership and department heads—such as finance, marketing, or operations—to identify key business questions, then direct their team to build models, dashboards, and reports that provide clear, predictive, and prescriptive answers. They are also responsible for mentoring their team, managing budgets for data projects, and championing a data-driven culture throughout the organization. To excel in Manager Data & Analytics jobs, a specific blend of technical acumen and soft skills is required. Typically, candidates possess a strong background in quantitative fields (e.g., Computer Science, Statistics, Engineering, or Business Analytics) and have 5+ years of progressive experience, including direct people management. Technical proficiency often includes SQL, Python or R, a deep understanding of data modeling, ETL processes, and visualization principles. However, the role demands far more than technical skill. Exceptional communication and storytelling abilities are paramount to explain complex findings to non-technical stakeholders. Strategic thinking, business acumen, project management, and a proven ability to drive organizational change are the hallmarks of a successful leader in this space. As businesses increasingly rely on data as a core asset, these managers are the critical architects of that future, making these roles both challenging and highly rewarding for those who can bridge the gap between data potential and business value.

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