Data Solutions Director

Key Responsibilities:

• Solution Design & Product Ownership (50%):
• Lead the design and architecture of innovative AI and Data Engineering solutions for Rackspace’s enterprise customers, leveraging cloud-native tools on AWS, Azure, or GCP. This includes defining roadmap, features, and functionalities as well as demo flows.
• Act as the Product Owner for these solutions, guiding development teams (while not directly coding) to ensure alignment with business objectives and market needs. This involves managing backlogs, prioritizing features, and ensuring timely delivery.
• Develop solution documentation to support selling and positioning, including high-level designs, architecture diagrams, and solution briefs.
• Stay abreast of the latest advancements in AI/ML and Data Engineering, identifying opportunities to enhance Rackspace’s solution offerings.
• Contribute to the development of Rackspace intellectual property, such as white papers and presentations.
• Presales & Enterprise Account Management (50%):
• Serve as the presales lead for named enterprise accounts, positioning and selling the designed AI and Data Engineering solutions.
• Build and maintain strong relationships with key stakeholders across various customer teams (Business Owners, Business Analytics, Data Engineering, Application Development, End Users, and Management).
• Conduct consultative engagements to understand customer business challenges and map them to appropriate Rackspace solutions.
• Develop compelling proposals, Statements of Work (SOWs), business cases, and RFP responses.
• Collaborate with the sales team to develop account prioritization and support strategies that foster long-term relationships.
• Participate in sales planning and forecasting activities.

Qualifications:

• Deep experience in either AI/ML or Data Engineering (cross-functional experience highly preferred).
• At least 5 years of experience as a senior-level data scientist or data architect, with demonstrable success delivering 5+ full-scale data projects utilizing cloud-native tooling on AWS, Azure, or GCP.
• Proficiency in relevant programming languages such as Python, PySpark, and SQL. Experience with deep learning libraries (TensorFlow/PyTorch), Spark/Hadoop is useful.
• Strong understanding of statistical modeling, machine learning algorithms, and NLP/NLU techniques.
• Proven ability to communicate complex technical concepts to both technical and non-technical audiences.
• Excellent presentation, whiteboarding, and problem-solving skills.
• Demonstrated success in managing ambiguity, collaborating across departments, and exceeding expectations in fast-paced environments.
• Strong knowledge of technology and industry trends impacting enterprise data analytics decisions.
• Proven track record of success working through technical challenges within enterprise organizations.






• Other Requirements:
• Highly motivated self-starter and team player with demonstrated leadership abilities.
• Exceptional time management and prioritization skills.
• This is a highly visible role requiring a strategic thinker with strong technical skills and exceptional communication abilities. The successful candidate will play a critical role in shaping Rackspace’s future in the Analytics & AI space.