Principal Engineer

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 recom