Principal Data Architect (Product Intelligence)

About the role: The Product Intelligence team serves a critical role by providing business intelligence to the organization: we synthesize data sources across the company, delivering product usage and business insights that directly shape product strategy and decision-making. We are looking for a Principal Data Architect to lead our Product Intelligence data function and to bring your experience and vision in enterprise data architecture, data modeling, and team leadership. You will own the strategy for bringing together disparate, company-wide data sources into a single, unified data lake, and will lead, develop, and mentor a team of data engineers to deliver on that vision. This is a highly strategic role: you will translate telemetry and usage data into product-led insights that identify upsell opportunities, predict churn, and help the business meet its revenue targets, and you will regularly manage senior stakeholders and present your data strategy directly to C-level management. We’re looking for someone with a strong data background who also understands the strategic importance of building an AI-ready data foundation. What you’ll do Own the enterprise data strategy and architecture, unifying disparate company-wide data sources into a single, unified data lake. Lead, develop, and mentor a team of data engineers, providing technical direction, coaching, and supporting their career growth. Partner with Product Management and business stakeholders to translate product usage and telemetry data into product-led insights – identifying upsell opportunities, predicting churn, and supporting revenue targets. Manage senior stakeholders across the business and regularly present data strategy, insights, and recommendations to C-level management. Own the technical architecture for data warehousing, data lake design, data modeling, and data access patterns. Drive the design and evolution of the analytics layer, including semantic modeling and dashboarding within BI tools. Champion an AI-ready data strategy, ensuring our data foundations, models, and governance are structured to support future AI and advanced analytics use cases. Establish data engineering standards, best practices, and measurable quality indicators to ensure high-quality, maintainable code. Ensure scalability, reliability, and performance of data platforms, pipelines, and analytics workloads. Promote an agile, iterative engineering culture and actively contribute to team ceremonies. Data Engineering Experience Master’s degree (or equivalent) in Computer Science, Engineering, or a related field. 8+ years of experience as a Data Engineer or Data Architect, including 3+ years leading, developing, and mentoring a team of data engineers. Proven track record designing and delivering unified data warehouse/data lake architectures that bring together disparate, company-wide data sources. Experience partnering with Product and business teams to deliver product-led insights, such as identifying upsell opportunities, predicting churn, or supporting revenue growth. Demonstrated experience managing senior stakeholders and presenting data strategy and insights to executive/C-level audiences. Strong expertise in database design, data modeling, and handling both structured and unstructured data. Strong system design and architectural skills, with the ability to design scalable data platforms. Proficiency in SQL and Python, with solid experience building and maintaining ETL/ELT pipelines. Familiarity with modern data stack tools such as dbt, AWS Lambda, Step Functions, Glue, Athena, Redshift, or similar. Experience with data visualization tools such as Power BI, QuickSight, Tableau, or similar. Practical knowledge of DevOps practices, CI/CD pipelines, and tools such as Git. Experience with containerization and infrastructure tools (e.g., Docker, Terraform, Jenkins). Hands-on experience with the AWS cloud platform. Proven ability to own projects end-to-end and operate with a high level of autonomy. Excellent communication and collaboration skills, with fluency in English. AI Awareness & Strategic Understanding Solid understanding of AI/ML and LLM concepts and their strategic implications for data architecture — hands-on experience building AI agents or RAG systems is a strong plus. Ability to identify where and how AI can create value across the data platform, and to architect data foundations (e.g., semantic layers, data quality, governance) that make the data lake AI-ready. Comfortable partnering with AI/ML practitioners or vendors to enable future AI-powered use cases, such as natural-language data exploration. We are the pioneers and trailblazers of a global IT Market Category (DEX) that is shaping the future of how the world works, giving our customers’ IT Teams total digital visibility across their enterprise. Our innovative solutions integrate real-time analytics, automation, and employee feedback across all endpoints. This enables our IT teams to solve comp…