Principal Engineer

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!

Requirements

• Experience : 11+yrs
• Extensive hands-on experience in Snowflake architecture, data platform engineering, and enterprise data solution design.
• Strong expertise in Snowflake account, warehouse, database, and schema design, including multi-cluster warehouses and multi-environment strategies.
• Advanced SQL skills, including complex queries, stored procedures, incremental processing, query profiling, and performance optimization.
• Strong Python programming skills for data processing, API integration, automation, and Snowflake development using Snowpark and libraries such as pandas.
• Working knowledge of SQL Server, including database concepts, SQL querying, and integration with enterprise data platforms.
• Hands-on experience with Azure Data Factory for data ingestion, orchestration, and integration workflows.
• Strong knowledge of Snowflake Dynamic Tables, Streams, Tasks, Snowpark, semantic views and models, Secure Data Sharing, cloning, Time Travel, replication, and failover.
• Proven experience with Snowflake governance capabilities, including RBAC, masking policies, row access policies, object tagging, tag-based masking, data classification, data quality monitoring functions (DMFs), Access History, and Object Dependencies.
• Strong understanding of dimensional modeling, Data Vault, hybrid modeling, and layered or medallion architecture patterns.
• Experience defining canonical keys, managing loosely typed source data, implementing deduplication, and preventing join fanout across related business domains.
• Expertise in ETL/ELT architecture and data pipeline development, with familiarity with dbt, Airflow, dbt Cloud, or native Snowflake Tasks.
• Experience integrating Salesforce CRM, market data feeds, third-party data sources, APIs, files, and streaming data into Snowflake.
• Understanding of Commercial Real Estate data domains, including property, building, lease, availability, sales, brokerage, valuations, capital markets, and property management.
• Experience integrating Snowflake with PostgreSQL, BI platforms such as Power BI, Tableau, or Looker, and application technologies such as Streamlit and React.
• Knowledge of geospatial data enrichment, property coordinates, and geocoding workflows.
• Strong understanding of enterprise security architecture, RBAC design, segregation of duties, PII protection, and regulatory requirements such as GDPR and CCPA.
• Experience with Snowflake network policies, PrivateLink, External Access Integrations, secure connectivity, and egress controls.
• Hands-on experience with Git-based deployment, Terraform or equivalent IaC tools, schemachange, dbt, and CI/CD pipelines using Azure DevOps, GitHub Actions, or similar platforms.
• Experience with environment promotion, release and rollback strategies, test-data cloning, operational monitoring, and alerting.
• Strong knowledge of at least one cloud platform, preferably Microsoft Azure, including storage, networking, virtual machines, identity, and key management services.
• Familiarity with containerization technologies such as Docker; experience with Snowpark Container Services is an advantage.
• Experience enabling semantic layers, natural-language querying, governed LLM access, and AI-powered analytics is desirable.
• Familiarity with Snowflake Cortex, feature-store architecture, machine learning data-access patterns, and agent-aware security controls is an advantage.
• Demonstrated architectural leadership, including design reviews, reference architecture development, standards enforcement, and mentoring data engineers.
• Strong stakeholder management skills, with the ability to collaborate across business, data, security, application, and infrastructure teams.
• Excellent communication skills, including the ability to explain architecture decisions, security controls, and cost-performance trade-offs to technical and non-technical stakeholders.
• Strong analytical and problem-solving abilities, with sound judgment in resolving ambiguous requirements, assessing risks, and recommending practical solutions.
• Demonstrated delivery management skills, including the ability to manage multiple initiatives, dependencies, and timelines across distributed teams.
• Relevant Snowflake, cloud architecture, or data engineering certifications are preferred.

Responsibilities

• Own the end-to-end Snowflake platform architecture, including account and organization topology, databases, schemas, virtual warehouses, and development, UAT, and production environments.
• Design and implement scalable data architecture and layered data models, including raw, staging, curated, and semantic layers for Commercial Real Estate (CRE) domains such as property, lease, availability, sales, organization, and contact.
• Define semantic views and semantic models that expose governed, business-friendly data for BI reporting, natural-language querying, and LLM-powered analytics.
• Establish warehouse sizing, scaling, workload isolation, naming conventions, object ownership, and reusable architecture standards.
• Define dimensional, Data Vault, or hybrid data models and canonical join keys to ensure data consistency and prevent duplicate records and join fanout across property, lease, and sales domains.
• Lead ETL/ELT pipeline architecture for batch and streaming ingestion from Salesforce CRM, market data feeds, APIs, files, and third-party CRE data providers.
• Leverage Snowflake Dynamic Tables, Streams, Tasks, and Snowpark to implement transformations, incremental processing, and automated data workflows.
• Establish data engineering standards for data typing, casting, deduplication, data quality, and handling wide or loosely typed source tables.
• Design and implement Snowflake security architecture, including role-based access control (RBAC), role hierarchies, functional access roles, and segregation of duties.
• Implement data protection controls such as column-level masking, row access policies, object tagging, tag-based masking, sensitive-data classification, and auditing.
• Ensure compliance with GDPR, CCPA, client confidentiality requirements, and restrictions governing personally identifiable information (PII) and confidential deal data.
• Define network security, secure connectivity, egress controls, External Access Integrations, and secure data-sharing patterns.
• Design integration architectures between Snowflake, PostgreSQL, downstream applications, BI tools, and application layers such as Streamlit and React.
• Govern Secure Data Sharing and provider-consumer data exchange with brokers, partners, and external data providers.
• Oversee geospatial and market-data enrichment pipelines, including property coordinates and geocoding, while ensuring compliance with network and data security restrictions.
• Optimize Snowflake query performance using clustering keys, search optimization, partition pruning, and result and metadata caching.
• Establish FinOps practices covering warehouse auto-suspend and auto-resume, resource monitors, budget controls, credit consumption, and cost attribution by project or cost center.
• Define platform SLAs, monitoring, alerting, capacity planning, and operational procedures, including tracking serverless compute costs.
• Enable AI-driven analytics and natural-language querying through governed semantic models and Snowflake Cortex where appropriate.
• Collaborate with data science teams to support feature stores, machine learning data access, and secure access to sensitive data attributes.
• Ensure LLMs and AI agents respect masking policies, row-level security, and appropriate access controls.
• Establish Infrastructure-as-Code (IaC), Git-based deployment, and CI/CD practices for Snowflake objects and semantic models using Terraform, schemachange, dbt, or equivalent tools.
• Define environment promotion, test-data cloning, release management, rollback procedures, and deployment standards.
• Implement observability using Snowflake query history, Account Usage views, Information Schema, logging, and alerting, supported by operational runbooks.
• Own the Snowflake platform roadmap, evaluate new features and editions, and establish reference architectures and engineering standards.
• Act as the technical design authority by conducting architecture reviews, mentoring engineers, enforcing best practices, and guiding implementation decisions.
• Translate business requirements across brokerage, valuations, capital markets, and property management into scalable data platform capabilities.
• Collaborate with business, security, infrastructure, application, and data engineering teams to communicate architecture trade-offs, performance considerations, and cost implications.

Bachelor’s or master’s degree in computer science, Information Technology, or a related field.