Governance Lead /Data Architect

Job Title: Data Architect / Governance Lead Location: Ahmedabad, Gujarat / Remote Job Type: Full-Time Department: Data & Analytics About Simform Simform is a premier digital engineering company specializing in Cloud, Data, AI/ML, and Experience Engineering to create seamless digital experiences and scalable products. Simform is a strong partner of Microsoft, AWS, Google Cloud, and Databricks, with a global presence and a strong focus on delivering high-quality engineering solutions for clients across North America, the UK, and Northern Europe. Role Overview We are looking for a Data Architect / Governance Lead to provide strategic leadership and hands-on implementation for enterprise Data & AI Governance initiatives, particularly within financial services and lending environments. The role will own the governance operating model across Gold data products, semantic metrics, Master Data Management (MDM), ontology, BI, Machine Learning, and AI assets. This role combines enterprise-level decision-making authority with hands-on technical implementation. The successful candidate will define governance policies, ownership models, certification standards, security controls, metadata frameworks, and approval processes while also working directly with platforms such as Atlan, Snowflake, dbt, Dagster, SQL, Python, and Git-based CI/CD. The role will ensure governance is embedded into the creation, promotion, and consumption of data and AI assets rather than being treated as a post-delivery review process. Key Responsibilities Data & AI Governance Strategy Define and operationalize the enterprise Data & AI Governance framework across data products, analytics, BI, ML, and AI. Translate the Data & AI operating model into a practical governance charter, RACI, decision rights, governance forums, escalation mechanisms, and operating procedures. Establish governance policies covering Critical Data Elements (CDEs) Data sensitivity Persona classification Data quality tiers Regulatory and retention requirements Business-product classification Decision-intent classification Establish governance standards for data products, semantic metrics, dashboards, ML models, and AI assets. Define policies for certification, de-certification, change management, exception handling, evidence retention, and approval workflows. Establish separation-of-duties requirements and appropriate governance controls for critical data and analytics assets. Lead governance councils, executive KPI reviews, control-violation escalations, and governance decision forums. Provide final governance sign-off for assets and initiatives falling within defined governance scope. Data Product & Asset Governance Establish certification policies and lifecycle management for: Gold Core Data Products Domain Data Products Consumer Serving Models Semantic Metrics BI Dashboards ML Models AI Assets Ensure Tier 0 and other critical assets have clearly assigned owners and stewards. Establish mandatory metadata, lineage, certification, and ownership requirements. Control duplication of data products, metrics, and analytical assets across the enterprise. Define and implement governance gates to prevent production promotion without required approvals and evidence. Establish asset-level change controls and assess potential downstream impact or blast radius before significant changes. Ensure governance evidence is attributable, reproducible, and audit-ready. Data Catalog & Metadata Governance Configure and manage Atlan domains, data products, glossary, ownership, classifications, custom metadata, lineage, and certification lifecycle states. Develop and maintain an enterprise business glossary, ontology, controlled taxonomies, and metadata standards. Establish ownership and stewardship registries across data products and business domains. Maintain structured registries for Data products Personas Metrics Regulatory and retention rules Approval policies Business definitions Ensure metadata is consistently captured and propagated across the data ecosystem. Integrate governance metadata with data engineering and analytics workflows. Establish catalog synchronization and metadata quality controls. Data Security & Access Governance Design and review Snowflake data governance and security controls. Work with Snowflake tags Masking policies RBAC / ABAC Row-level access controls Column-level access controls Audit logging Metadata propagation Ensure sensitive and regulated data is appropriately classified and protected. Define governance requirements for persona-based access and controlled consumption of data products. Review access models and security controls for alignment with enterprise governance policies. Establish appropriate audit and monitoring mechanisms for governed data assets. Governance .