Company Description 👋🏼We're Nagarro. We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at a scale — across all devices and digital mediums, and our people exist everywhere in the world (18500+ experts across 39 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in! Job Description Requirements • Experience : 9+years • Strong experience in data architecture, data engineering, or enterprise data platforms, with substantial hands-on experience in Snowflake. • Strong expertise in Technology Architecture and Data Architecture, including solution design, data modeling, integration, and implementation of scalable enterprise platforms. • Strong hands-on experience with Snowflake security, data governance frameworks, access management, and compliance controls. • Proficiency in Snowflake Row Access Policies (RAP), Role-Based Access Control (RBAC), role hierarchies, least-privilege permissions, dynamic data masking, and tag-based masking policies. • Experience enforcing access controls at database, schema, object, row, and column levels. • Strong understanding of data ownership, stewardship, classification, metadata management, data lineage, data quality, and audit requirements. • Strong SQL skills, including complex queries, stored procedures, incremental processing, and query performance tuning. • Strong Python programming skills for data processing, API integration, automation, and pipeline development. • Experience with PostgreSQL and enterprise database architecture, including data modeling, integration, and performance optimization. • Hands-on experience with Streamlit application development and Snowflake Cortex capabilities, including Cortex Analyst, Cortex Search, Cortex Agents, and semantic modeling. • Ability to evaluate AI-generated responses and implement appropriate security and governance controls for AI applications. • Experience building and managing data ingestion and transformation pipelines using Azure Data Factory, AWS Glue, Python, or equivalent tools. • Strong understanding of full loads, incremental loads, CDC, data validation, error handling, and pipeline monitoring. • Familiarity with AWS services such as S3 and IAM, including secure integration with Snowflake. • Experience using Git, Azure DevOps, and CI/CD pipelines to version, review, test, and deploy database objects, security policies, and application changes across environments. • Knowledge of data privacy, PII protection, access reviews, audit evidence, data retention, and regulatory compliance requirements. • Strong architectural leadership skills, with the ability to define standards, evaluate design decisions, and guide technical teams toward secure and maintainable solutions. • Excellent communication and stakeholder management skills, with the ability to explain complex architecture, governance, security, and AI concepts to technical and business audiences. • Strong analytical and problem-solving abilities, including the capacity to clarify ambiguous requirements, identify risks, and recommend practical solutions. • Ability to manage multiple initiatives, dependencies, and timelines while collaborating with distributed teams. • Experience mentoring engineers and driving technical excellence across data architecture and engineering teams. • PL/SQL knowledge is desirable. • Relevant Snowflake, cloud, or data architecture certifications are preferred. Responsibilities • Define, implement, and maintain enterprise data governance standards covering data ownership, stewardship, classification, metadata, lineage, data quality, and compliance. • Design and implement secure, scalable Snowflake data architectures aligned with enterprise architecture and security standards. • Develop and maintain Snowflake Row Access Policies (RAP) to control data visibility based on region, market, business unit, and user entitlements. • Implement Role-Based Access Control (RBAC), role hierarchies, least-privilege access, and database-level permissions. • Protect sensitive and personally identifiable information (PII) using dynamic data masking, tag-based masking policies, and column-level security. • Enforce access controls across database, schema, object, row, and column levels. • Establish access reviews, audit monitoring, secure authentication, and integration practices to meet organizational privacy, retention, and compliance requirements. • Design scalable data models and provide architectural guidance on data integration, SQL optimization, and Snowflake performance tuning. • Develop and optimize SQL and Python solutions for data processing, automation, integration, and incremental data processing. • Build and maintain reliable data ingestion and transformation pipelines using Python, Azure Data Factory, AWS Glue, or equivalent technologies. • Implement full-load, incremental-load, and Change Data Capture (CDC) processes with appropriate data validation, error handling, and pipeline monitoring. • Develop interactive Streamlit applications to enable analytics and conversational access to enterprise data. • Implement Snowflake Cortex Analyst, Cortex Search, Cortex Agents, and semantic models to support natural-language queries, information retrieval, and AI-driven analytics. • Evaluate AI response accuracy and ensure appropriate data governance, security, and access controls within AI-enabled applications. • Analyze Snowflake query profiles, optimize warehouse utilization, and balance performance with cost efficiency. • Automate the deployment of database objects, security policies, and application changes using Git, Azure DevOps, and CI/CD pipelines. • Integrate Snowflake securely with cloud services, including AWS S3 and IAM. • Collaborate with business stakeholders, data owners, security teams, governance teams, and engineering teams to establish and enforce architecture standards. • Lead solution design, assess technical risks, resolve architectural challenges, and guide implementation decisions across enterprise data initiatives. • Mentor engineers, review technical designs, and promote secure, scalable, maintainable, and compliant data solutions. • Manage multiple initiatives, dependencies, and delivery timelines while ensuring alignment with business and technology objectives. Qualifications Bachelor’s or master’s degree in computer science, Information Technology, or a related field.