About the job

Role Overview :

We are seeking a Senior Snowflake Data Engineer to design, develop, and maintain scalable data platform solutions for the Pacific Data Platform. The role covers end-to-end data ingestion, transformation, data modeling, performance optimization, security, and data quality. The role also involves developing AI-enabled solutions using Snowflake Cortex AI, Cortex Analyst, and Cortex Search to support natural-language analytics, intelligent search, and insights from structured and unstructured data.

Key Responsibilities :

Snowflake Data Engineering :

- Design and implement scalable Snowflake data architectures for storage, processing, reporting, analytics, and AI use cases and strong sql.

- Develop and maintain ETL/ELT pipelines using SQL, Python, Snowpark, SnapLogic, and/or Azure Data Factory.

- Integrate structured and semi-structured data from databases, APIs, enterprise applications, and files, and prepare unstructured content for AI processing.

- Implement full-load, incremental-load, and change data capture processes with appropriate validation, reconciliation, and error handling.

- Develop and maintain dimensional and relational data models that accurately represent business requirements.

- Build and optimize tables, views, stored procedures, tasks, streams, and dynamic tables where appropriate.

- Analyze query profiles and optimize warehouse sizing, clustering, partition pruning, and caching to improve performance and control costs.

- Review existing SQL and Python code to improve efficiency, security, robustness, and maintainability.

- Implement data quality checks for completeness, accuracy, consistency, validity, and duplication.

Snowflake AI and Cortex :

- Design and implement AI-enabled data solutions using Snowflake Cortex AI and Snowpark, Cortex Analyst, Cortex Search and Agent creation.

- Apply Cortex AI functions to relevant use cases such as text summarization, classification, information extraction, and data enrichment.

- Collaborate with business stakeholders to identify practical AI use cases across property, lease, availability, client, and market data.

Platform Operations and Collaboration :

- Implement Snowflake role-based access control, masking policies, row access policies, and auditing in line with enterprise security requirements.

- Monitor pipeline execution, data freshness, warehouse utilization, failures, and service performance.

- Establish logging, alerting, retry, and recovery mechanisms for reliable production operations.

- Maintain version-controlled code and support automated deployments through Git and Azure DevOps.

- Document architectures, data mappings, pipelines, semantic definitions, and operational procedures.

- Collaborate with application engineers, analysts, architects, and business stakeholders throughout delivery.

- Mentor junior engineers and promote engineering standards, code reviews, and continuous improvement.

Required Qualifications :

- Bachelor's or master's degree in Computer Science, Information Technology, Engineering, or a related field.

- 6 - 10 years of relevant experience in data engineering, database development, or cloud data platforms.

- Strong hands-on experience with Snowflake architecture, data loading, SQL development, performance optimization, and security.

- Advanced SQL skills, including complex joins, window functions, stored procedures, query profiling, and troubleshooting.

- Strong Python programming skills for data processing, automation, API integration, and error handling.

- Experience with Snowpark for data transformations and application integration.

- Experience building pipelines using Azure Data Factory, or comparable integration tools.

- Practical experience with Snowflake Cortex AI, Cortex Analyst, and Cortex Search.

- Ability to develop semantic views or semantic models with clear business definitions and validated analytical queries.

- Understanding of natural-language-to-SQL, semantic and keyword search, embeddings, text chunking, and RAG.

- Experience integrating Snowflake AI capabilities with applications using APIs or Python.