Data & AI Strategy - Senior Advisor

Company Description

Be part of a global consulting powerhouse, partnering with clients on their most critical strategic transformations.  ​

We are Wavestone. Energetic, solution-driven experts who focus as much on people as on performance and growth. Hand in hand, we share a deep desire to make a positive impact. We are an ambitious firm with a worldwide reach and an ever-expanding  portfolio of clients, topics, and projects. In North America, Wavestone operates from hubs in New York City, Pittsburgh, Dallas and Toronto. We work closely with CEOs and technology leaders to optimize IT strategy, sourcing models, and business processes and are committed to building lasting partnerships with our clients.​

Are you a true team player, living strong values? Are you a passionate learner, aiming to grow every day? Are you a driven go-getter, tackling challenges head-on? Then we could be the right fit for you. Join Wavestone and thrive in an environment that’s empowering, collaborative, and full of opportunities to turn today’s challenges into tomorrow’s solutions – contributing to one or more of our core 4 capabilities:​

Business Consulting Business Strategy & Transformation, Organizational Effectiveness & Change Management, Operating Model Design & Agility, Program Leadership & Project Management, Marketing, Innovation, & Customer Experience​ Technology Consulting IT Strategy & CTO Advisory, Technology Delivery, Data & Artificial Intelligence, Software & Application: Development & Integration, SAP Consulting, Insurance/Reinsurance​ Cybersecurity Cyber Transformation Remediation, Cyber Defense & Recovery, Digital Identity, Audit & Incident Response, Product & Industrial Cybersecurity​ ​Sourcing & Service Optimization Global Services Strategy, IT & Business Process Services Outsourcing, Global In-House Center Support, Services Optimization, Sourcing Program Management​

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Read more at www.wavestone.com.

Job Description

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 …