Senior Manager, Solutions Engineering - East

As Senior Manager, Solutions Engineering at Dataiku, you will play a critical role in driving the success of our sales and customer success efforts, with a focus on delivering highly technical, customer-facing engagements across the sales and customer lifecycle.

You will lead, mentor, and grow a team of Sales Engineers and Customer Success Engineers across the East region, working closely with the sales leadership to strategize on opportunities, provide technical expertise, and ensure the successful adoption of Dataiku’s platform in service of customer retention and upsell. Your leadership will empower the team to demonstrate the value of Dataiku to prospective customers and secure their confidence in our platform.

As a player-coach, you will balance the strategic oversight of team performance with active participation in high-profile opportunities, building strong internal relationships with sales, product management, customer success, and other cross-functional teams. You will be responsible for ensuring excellence in execution while fostering a collaborative and innovative environment that attracts top talent, drives customer satisfaction, and evangelies our technology.

How you’ll make an impact

• Serve as trusted technical advisor and the primary technical point of contact for sales leadership within the East region, aligning on sales strategy, providing technical insights, and communicating risks and opportunities in key customer engagements.
• Partner with sales teams to understand customer business challenges and articulate the value of Dataiku’s AI and analytics solutions.
• Engage directly with customers to lead technical discussions, demonstrate product value, and address concerns to drive adoption, retention, and satisfaction.
• Lead and manage a high-performing team of Solutions Engineers and Customer Success Engineers, ensuring technical success throughout the entire sales process.
• Foster an environment of continuous learning and improvement, enabling the team to scale with the business and meet evolving demands.
• Build strong relationships with cross-functional teams including sales, product management, tech, marketing, and customer success, ensuring alignment between pre- and post-sales activities.
• Provide feedback on product development and customer needs, helping to drive improvements in Dataiku’s platform.
• Collaborate with Solutions Engineering and Technical Enablement leadership to refine success metrics and track the effectiveness of enablement programs and initiatives.
• Support sales leadership in forecasting net new sales, upsells, and downsell, a process which includes documenting account retention risks.

What you’ll need to be successful

• At least 6 years of experience in Solutions Engineering, ideally with enterprise software products, including 2+ years of people management experience.
• Demonstrated success in leading technical teams, building high-performing groups, and driving customer success in complex, large-scale enterprise analytics deployments.
• Hands-on experience with the application of AI, machine learning, and analytics solutions across various industries and business challenges.
• Excellent communication, presentation, and public speaking skills, with the ability to engage with C-level executives and technical stakeholders alike.
• Strong coaching, mentoring, and leadership skills, with a proven track record of developing talent and driving team performance.
• Intellectual curiosity and a passion for the intersection of business and technology, with a track record of solving complex business challenges through technology.
• Experience building and enabling high performing teams.
• Geographic location on the East coast of the US.

What will make you stand out

• Familiarity with technologies such as SQL, NoSQL, Hadoop, Spark, cloud computing platforms (AWS, Azure, GCP), and containerization (Kubernetes, Docker).
• Proficiency in programming languages such as Python, R, and SQL.
• Understanding of machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, as well as orchestration tools like Kubeflow or Airflow.
• Experience with the full machine learning lifecycle: feature engineering, model training, deployment, and scoring.
• Familiarity with entire sales lifecycle, including leading technical resources through adoption.