Requirements

Expected technologies

AWS

data architecture

data engineering

data management

enterprise data modeling

data governance

ML/AI

SDLC

Data Security

Operating system

Windows

macOS

Our requirements

• Strong technical background in data architecture, data engineering, and data management
• Proven experience in enterprise data modeling, data governance, and data integration
• Familiarity with the ML/AI lifecycle and enabling data platforms for intelligent applications
• Effective communication and synthesis skills to engage confidently with both technical and non‑technical stakeholders
• Experience with solution architecture and cross‑domain data initiatives
• Ability to influence and align technical solutions with business goals, while collaborating respectfully with diverse teams
• Strong understanding of modern data platforms, cloud‑native data services, and data security practices
• Commitment to building an inclusive, supportive environment where all voices and perspectives are welcomed

Your responsibilities

📌 Responsibilities

You will contribute to the implementation and governance of the enterprise data architecture, ensuring alignment with business and technical strategies. You will support the definition and maintenance of the enterprise data model, promoting consistency and interoperability across domains. You will help establish and enforce data policies, integration patterns, and data contracts between domains and capabilities. You will collaborate with domain architects, engineering leaders, and product teams to simplify and standardize data flows and interfaces. You will support the full ML/AI lifecycle, from data acquisition and preparation to model deployment and monitoring. You will contribute to architecture roadmaps, principles, and standards related to data. You will participate in resolving complex data-related architectural decisions and challenges. You will help improve the maturity of data architecture assets and practices across the organization. You will help create an inclusive culture where all team members feel heard, valued, and empowered to contribute.

📌 Key stakeholders

VP of Architecture Engineering Directors & Managers Product Directors & Managers Domain Architects Principal & Staff Engineers Data Scientists & ML Engineers Business stakeholders and colleagues across diverse teams and backgrounds

📌 Key performance indicators

Delivery of data architecture milestones Health and adoption of the enterprise data model Quality and consistency of data contracts and integration patterns Support for ML/AI lifecycle and data platform scalability Engineering and data governance health Delivery of OKRs Contribution to an inclusive, supportive, and collaborative work environment