Data Architecture Leadership:
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Design and evolve enterprise-grade data architectures to support subscription analytics, customer lifecycle insights, and AI/ML applications.
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Define and implement data modeling standards, governance frameworks, and integration strategies across cloud and hybrid environments.
Subscription Analytics Enablement:
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Architect data pipelines and analytical models to support metrics such as ARR, churn, renewal rates, customer health scores, and usage patterns.
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Collaborate with product, finance, and commercial teams to align data structures with subscription KPIs and business outcomes.
AI & Advanced Analytics:
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Partner with data science teams to operationalize machine learning models for predictive analytics, customer segmentation, and recommendation engines.
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Ensure scalable deployment of AI solutions across platforms, enabling real-time decision-making and automation.
Platform & Tooling Strategy:
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Lead the selection and implementation of modern data platforms (e.g., AWS, Azure, etc) and orchestration tools.
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Lead continuous improvement and refactoring approach to keep the tech stack optimized for performance and costs.
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Drive adoption of self-service analytics capabilities for business users through semantic layers and intuitive data access.
Governance & Compliance:
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Establish robust data governance practices ensuring data quality, lineage, privacy, and compliance with global standards (e.g., GDPR, HIPAA).
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Champion metadata management and cataloging to enhance data discoverability and trust.
Mentorship & Collaboration:
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Mentor data engineers and architects, fostering a culture of innovation, excellence, and continuous learning.
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Collaborate with enterprise architects, product owners, and business stakeholders to align data strategy with organizational goals.
Required Qualifications:
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Overall 15+ years of experience
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Minimum 10+ years in data architecture, with a strong background in subscription analytics and AI/ML.
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Proven ability to design and implement cloud-based data platforms using modern tools and technologies.
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Solid understanding of subscription business models, SaaS metrics, and customer insights.
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Hands-on experience with data engineering tools (e.g., Spark), cloud platforms (Azure, AWS, GCP), and data modeling.
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Familiarity with streaming data architectures and AI/ML deployment practices (MLOps).
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Strong communication and stakeholder engagement skills.
Bachelor s or Master s degree in Computer Science, Data Engineering, or a related field.
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Demonstrated leadership and strategic thinking, with the ability to translate complex technical concepts into business value.
Desired Characteristics:
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Proven ability to lead and mentor teams, fostering a collaborative and high-performance culture focused on innovation and excellence.
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Excellent interpersonal, communication, and presentation skills with the ability to collaborate effectively across diverse teams.
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Act as a trusted advisor to executive stakeholders, offering insights, recommendations, and solutions to address business challenges and drive competitive advantage.
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Strong analytical and problem-solving skills using data-based decisions, combined with a passion for improving patient care and clinical research.
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Experience with Agile methodologies and product management tools.