Data & Insights Strategy Lead
3 days ago
- Data Infrastructure & Architecture
- Develop and oversee enterprise-level data frameworks including data lakes, warehouses, and cloud-based storage solutions.
- Create and manage scalable data models and schemas to support real-time and historical reporting.
- Define and implement data governance standards, ensuring data quality, integrity, and compliance across systems.
- Lead the delivery of data analytics initiatives by developing dashboards, reports, and visualizations to surface actionable business insights.
- Identify key trends and metrics that inform strategic and operational planning.
- Partner with internal stakeholders to translate business needs into technical solutions.
- Manage a multidisciplinary team of data professionals, including engineers, analysts, and BI developers.
- Assign priorities, oversee timelines, and ensure deliverables align with business objectives.
- Foster a high-performance team culture through continuous coaching and knowledge sharing.
- Evaluate and implement emerging technologies to enhance data analytics capabilities and automation.
- Champion the adoption of AI, machine learning, and predictive analytics for advanced business use cases.
- Keep current with global trends in cloud platforms, data engineering, and data science.
- Establish and maintain data lifecycle and governance processes aligned with internal policies and external regulations.
- Perform periodic reviews of systems for data accuracy, security, and consistency.
- Drive initiatives for data standardization, classification, and stewardship.
- Develop and oversee enterprise-level data frameworks including data lakes, warehouses, and cloud-based storage solutions.
- Bachelors degree in Computer Science, Information Management, or a related technical field; Master's degree is an advantage.
- Minimum of 5 years' progressive experience in data management, analytics, or enterprise data architecture.
- Proven leadership experience in building and managing high-performing data teams.
- Strong background in SQL, data modeling, and ETL frameworks.
- Hands-on experience with cloud data platforms such as Azure, AWS, or GCP.
- Proficiency in BI tools like Power BI, Tableau, or equivalent.
- Working knowledge of data privacy regulations and compliance best practices.
- Excellent stakeholder communication, analytical thinking, and problem-solving skills.
Preferred Skills & Certifications:
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Industry certifications in data architecture, analytics, or cloud technologies (e.g., AWS Data Specialty, Microsoft Certified: Data Engineer).
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Practical experience with Python, R, or other scripting languages for data analysis.
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Exposure to AI/ML use cases in a business intelligence context.
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