Practice Director - Data Engineering and AI/ML

Practice Directors are expected to be visionary leaders and subject matter experts, capable of driving success in the Data Engineering, Analytics, and AI/ML practice. This role encompasses delivering strategic and technical expertise in customer engagements while ensuring the overall growth and excellence of the practice. 

As an experienced Practice Director with a proven ability to manage and execute professional services engagements, you will lead initiatives focused on Data Modernization, AI/ML, and intelligent product development. Successful candidates will demonstrate strategic thinking, develop innovative data solution strategies, align complex technical objectives with business goals, and deliver measurable outcomes. You will inspire and mobilize resources, providing technical guidance while fostering collaboration and innovation. Passion for cutting-edge technology, cloud adoption, and analytics is critical to thrive in this role. 

As a director, you will lead a team of Data Engineers, Data Architects, and Machine Learning professionals, mentoring and guiding their development. Beyond team leadership, you will champion practice goals, ensuring high-quality and efficient delivery, supporting sales efforts, shaping project opportunities, and managing operational priorities like resource allocation and hiring. Strong communication skills, a collaborative mindset, and the ability to inspire trust and innovation are essential to succeeding in this role. 

• Extensive Leadership Experience: 15+ years of leadership, with a strong track record of 12+ years in the consulting industry. 
• Business Line Oversight: Proven experience managing a business line and P&L 
• Expertise in Data AI and Technology Solutions: Demonstrated ability to lead analysis, architecture, design, and development of cloud Data and AI and technology solutions, including process redesign, change management, and strategic alignment. 
• Cross-Capability Implementation: Experience delivering business advisory services, Data and AI solutions, and technology integrations. 
• Depth in Data and AI Domains: Expertise in Data and AI/ML engineering, data science, and analytics consulting, with comprehensive knowledge across Data and AI disciplines. 
• Team Management: Skilled in managing senior-level teams and driving their development and performance. 
• Strategic Advisor: Strong ability to act as a trusted advisor to clients and stakeholders. 
• Financial Acumen: Proven experience in financial management and successfully operating a business. 
• Engagement Leadership: Proficiency in leading transformation projects involving change management, organizational design, process mapping, data strategy/analysis, and technology implementation. 
• Executive Presence: Exceptional communication skills and the ability to establish trusted relationships with C-level executives. 
• Organizational Excellence: Mastery in promoting organizational innovation, collaboration, and continuous improvement through dynamic leadership. 
• High-Stakes Engagements: Experience in leading strategic pursuits for key accounts and capability-focused deals. 
• Cloud and Agile Expertise: Deep experience in cloud-based Data engineering, Artificial Intelligence, Machine Learning, and Agile delivery, ensuring efficient, scalable, and innovative solutions. 
• Delivery Leadership: Ability to shape and lead delivery teams from architectural design to project inception, ensuring alignment with client objectives and high-quality outcomes 

• Practice Building: Spearhead the growth of the practice area by developing innovative strategies for business development, talent management, and project delivery. Cultivate thought leadership by creating best practices, reusable assets, case studies, and solution frameworks that differentiate the practice in the market. 
• Strategic Vision: Define and communicate a compelling vision for the practice, aligning with organizational goals and market opportunities to position the team as a leader in data and analytics. 
• Accountability: Own all aspects of practice growth, including driving sales, recruiting top talent, managing client accounts, overseeing consulting engagements, and ensuring operational excellence across the practice. 

• Leadership Development: Build a team of high-performing leaders and technical experts by mentoring and coaching individuals to grow their skills and take on greater responsibilities. Encourage innovation and a growth mindset among team members. 
• Team Building: Create a collaborative and inclusive culture that fosters engagement, trust, and continuous learning. Lead recruiting efforts to attract and retain top talent while supporting onboarding to ensure a smooth transition into the team. 
• Technical Excellence: Provide thought leadership in data and analytics, ensuring the team stays ahead of industry trends and maintains technical expertise in emerging technologies, tools, and methodologies. 

• Project Oversight: Manage engagement risks and project economics, including detailed planning, budgeting, and monitoring of accounts receivable. Define project deliverables clearly and ensure alignment with client objectives and expectations. 
• Client Satisfaction: Maintain high levels of client satisfaction by delivering impactful solutions and building trust at the highest levels of client organizations. Foster long-term client relationships by consistently exceeding expectations. 
• Governance: Oversee the successful execution of all projects within the data and analytics portfolio, ensuring alignment with the practice’s standards for quality and delivery excellence. 

• Opportunity Identification: Identify growth opportunities by analyzing market trends, client needs, and competitive dynamics. Develop innovative offerings that meet evolving demands in data and analytics. 
• Strategic Partnerships: Build and nurture relationships with technology partners to co-develop and sell joint solutions. Actively engage with local market teams to align on sales strategies, resource capacity, and technical capabilities. 
• Relationship Management: Cultivate strong relationships with C-suite executives and other key client stakeholders, positioning the organization as a trusted advisor. Partner with leadership to guide business development activities and expand the client portfolio. 

• Solution Architecture: Design and implement scalable data architectures for machine learning pipelines, automation frameworks, and CI/CD processes to solve complex client challenges. Deliver robust solutions tailored to specific use cases and industries. 
• Innovative Thinking: Lead the exploration of emerging technologies and methodologies in data Engineering, data science, machine learning, and artificial intelligence. Consistently push the boundaries of what’s possible to deliver cutting-edge solutions to clients. 
• Thought Leadership: Develop and disseminate thought leadership through whitepapers, blogs, conference presentations, and workshops. Position the organization as a leader in the analytics and machine learning domains. 

• Client Engagement: Collaborate closely with clients to understand their needs, shape project objectives, and define a clear roadmap for delivery. Leverage Agile methodologies to ensure efficient execution and client satisfaction. 
• Cross-Functional Collaboration: Work with stakeholders across internal teams, technology partners, and clients to develop and deliver cohesive solutions that address both technical and business requirements. 
• Pre-Sales Support: Partner with sales teams during the pre-sales process to provide technical insights and ensure alignment with the client’s vision and goals. 

• Community Building: Promote a sense of community by organizing and participating in knowledge-sharing initiatives, technical meetups, and workshops. Encourage team members to contribute to industry forums and internal communities of practice. 
• Knowledge Sharing: Share learnings and best practices from engagements with the broader organization to build a collective repository of insights and expertise. 

• Flexibility: Demonstrate a willingness to travel up to 50% during peak periods, supporting client engagements, business development opportunities, and team initiatives as needed 

• This role is not sponsorship eligible
• Candidates need to be legally allowed to work in the US for any employer

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