Principal - Data Products & Solutions

About the Role

Key Responsibilities

• Drive the technical design, development, and delivery of cross-domain data products integrating data from multiple domains (e.g., CRM, ERP, IoT, operational systems).
• Ensure data product architectures align with enterprise data strategy and promote reuse, scalability, and standardization.
• Work with business and analytics teams to understand requirements and translate them into actionable data solutions and APIs.
• Contribute to the definition and adoption of data product standards (semantic models, APIs, metrics) across domains.
• Develop technical solutions leveraging cloud-native platforms (e.g., GCP, AWS, Azure) that meet business and operational needs.
• Collaborate with platform engineering and domain data teams to implement ingestion, transformation, orchestration, and monitoring patterns.
• Support data scientists and AI/ML engineers by designing data products that enable advanced analytics and machine learning solutions (e.g., AssetBrain, CustomerBrain).
• Serve as a key technical advisor to domain engineering teams and cross-functional partners.
• Advocate for a data product mindset and promote data democratization through well-governed, discoverable, and high-quality data products.
• Ensure that data products meet enterprise governance, data privacy, security, and compliance requirements.
• Incorporate metadata, lineage, and quality controls in all data product designs.

Requirements

• Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or related field.
• 10+ years of experience in data engineering, solution engineering, or architecture roles, including experience designing and delivering data products.
• Hands-on experience with enterprise-scale data solutions, ideally in data center, cloud infrastructure, or technology companies.
• Strong understanding of data governance, quality, and compliance standards.
• Ability to translate complex data requirements into high-quality technical designs that deliver business value.

Nice to Have

• Experience with data products such as Customer360, Product360, Asset360, or similar cross-domain solutions.
• Cloud certifications (e.g., Google Professional Data Engineer, AWS Big Data Specialty).
• Experience delivering analytics self-service capabilities, conversational analytics, and enterprise dashboards using BI tools (e.g., Looker, Power BI, Tableau).
• Familiarity with AI/ML operationalization, including enabling data pipelines for AI/ML model development and deployment.
• Knowledge of data mesh principles or federated data architectures.
• Experience with cost optimization and cloud resource management for data workloads.

Qualifications

• Bachelor's or Master's degree in relevant fields.
• 10+ years of experience in data-related roles.