Job DescriptionThe
Data Governance & AI Architect will lead the design and implementation of enterprise-grade data and AI platforms, ensuring they are scalable, secure, governed, and ethically aligned. This role requires deep technical expertise in data engineering, combined with strategic leadership in data governance and AI architecture. The ideal candidate will be a systems thinker who can bridge business needs with technical execution, enabling innovation while ensuring compliance and trust.
Responsibilities- Data Architecture & Engineering
- Design and evolve modern data architectures including data lakehouses, data mesh, and real-time streaming systems.
- Lead the development of scalable data pipelines and integration frameworks using tools like Databricks, Spark, Airflow, and Kafka.
- Define data modeling standards and ensure alignment with governance, privacy, and compliance requirements.
- Optimize data infrastructure for performance, reliability, and cost-efficiency across cloud platforms.
- Data Governance
- Collaborate with data governance teams to embed policies, standards, and controls into data and AI architecture.
- Ensure data lineage, metadata management, and data quality frameworks are integrated into platform design.
- Support regulatory compliance and internal governance initiatives.
- Promote data stewardship and ownership models across business and technical domains.
- AI Architecture
- Architect end-to-end AI/ML platforms, including feature stores, model training environments, deployment pipelines, and monitoring systems.
- Implement MLOps best practices for model lifecycle management, CI/CD, and performance tracking.
- Ensure AI systems are designed for scalability, explainability, and ethical use.
- Integrate AI solutions with cloud-native services (e.g., Azure ML, AWS SageMaker, GCP Vertex AI).
- Security & Responsible AI
- Partner with cybersecurity and legal teams to ensure data and AI systems meet security and ethical standards.
- Implement controls for data access, encryption, and model transparency.
- Support responsible AI practices including bias detection, fairness, and accountability.
- Collaboration & Leadership
- Work cross-functionally with analytics, governance, security, and business teams to align architecture with strategic goals.
- Mentor data engineers and ML engineers, promoting engineering excellence and architectural best practices.
- Evaluate emerging technologies and trends to inform innovation and investment.
Qualifications- Bachelor's or Master's degree in Computer Science, Data Engineering, AI, or related field.
- 8+ years of experience in data engineering, architecture, and AI systems design.
- Proven experience building and scaling enterprise data and AI platforms with governance and security integration.
- Deep expertise in cloud platforms (Azure, AWS, GCP), big data technologies, and ML frameworks.
- Strong understanding of data governance, privacy regulations, and responsible AI principles.
- Excellent communication, stakeholder engagement, and strategic planning skills.
- Preferred Skills:
- Experience in regulated industries (e.g., healthcare, finance, sustainability).
- Certifications in cloud architecture, data governance, or AI/ML (e.g., Azure Solutions Architect, Responsible AI).
- Familiarity with tools like Snowflake, Databricks, MLflow, Apache Kafka, Microsoft Purview, and Collibra.
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