Manager - Data & Strategy

As a Data & Strategy Engineer at a manager level at Wavestone, you will be expected to help address strategic as well as detailed client needs, specifically serving as a trusted advisor to C-level executives and be comfortable supporting and leading hands-on data projects with technical teams. 

In this role you would be leading or supporting high-impact data transformation, data modernization and data initiatives to accelerate and enable AI solutions, bridging business strategy and technical execution. You will architect and deliver robust, scalable data solutions, while mentoring teams and helping to shape the firm’s data consulting offerings and skills. This role requires a unique blend of strategic vision, technical depth, and consulting leadership.

Key Responsibilities

• Lead complex client engagements in data engineering, analytics, and digital transformation, from strategy through hands-on implementation.
• Advise C-level and senior stakeholders on data strategy, architecture, governance, and technology adoption to drive measurable business value.
• Architect and implement enterprise-scale data platforms, pipelines, and cloud-native solutions (Azure, AWS, Snowflake, Databricks, etc.).
• Oversee and optimize ETL/ELT processes, data integration, and data quality frameworks for large, complex organizations.
• Translate business objectives into actionable technical road maps, balancing innovation, scalability, and operational excellence.
• Mentor and develop consultants and client teams, fostering a culture of technical excellence, continuous learning, and high performance.
• Drive business development by shaping proposals, leading client pitches, and contributing to thought leadership and market offerings.
• Stay at the forefront of emerging technologies and industry trends in data engineering, AI/ML, and cloud platforms.

Key Competencies & Skills

• Strategic Data Leadership: Proven ability to set and execute data strategy, governance, and architecture at the enterprise level.
• Advanced Data Engineering: Deep hands-on experience designing, building, and optimizing data pipelines and architectures (Python, SQL, Spark, Databricks, Snowflake, Azure, AWS, etc.).
• Designing Data Models: Experience creating conceptual, logical, and physical data models that leverage different data modeling concepts and methodologies (normalization/denormalization, dimensional typing, data vault methodology, partitioning/embedding strategies, etc.) to meet solution requirements. 
• Cloud Data Platforms: Expertise in architecting and deploying solutions on leading cloud platforms (Azure, AWS, GCP, Snowflake).
• Data Governance & Quality: Mastery of data management, MDM, data quality, and regulatory compliance (e.g., IFRS17, GDPR).
• Analytics & AI Enablement: Experience enabling advanced analytics, BI, and AI/ML initiatives in complex environments.
• Executive Stakeholder Management: Ability to communicate and influence at the C-suite and senior leadership level.
• Project & Team Leadership: Demonstrated success managing project delivery, budgets, and cross-functional teams in a consulting context.
• Continuous Learning & Innovation: Commitment to staying ahead of industry trends and fostering innovation within teams.