Senior Snowflake Data Engineer

Senior Snowflake Data Engineer Position Overview We are seeking a highly skilled Senior Snowflake Data Engineer with 7+ years of experience to design, build, and optimize pipelines for client Snowflake development. This role demands expertise in dbt (data build tool) for test-driven development, strong SQL and Python programming skills, and a deep understanding of DevOps practices. The ideal candidate will have hands-on experience optimizing Snowflake data pipelines and implementing robust, scalable data solutions using modern engineering practices. Key Responsibilities Data Pipeline Development & Optimization

• Design, develop, and optimize high-performance data pipelines in Snowflake
• Implement and maintain dbt models with comprehensive testing and documentation
• Apply test-driven development patterns using dbt tests, including data quality checks and schema tests
• Optimize existing pipelines to reduce processing time and Snowflake compute costs
• Build incremental models and implement efficient data loading strategies
• Create and maintain data transformation workflows using SQL and Python dbt Development & Testing
• Build modular, reusable dbt models following best practices and style guides
• Implement comprehensive testing strategies including unit tests, data tests, and schema tests
• Create and maintain dbt documentation for data lineage and business logic
• Develop custom dbt macros for reusable transformations and testing patterns
• Configure and optimize dbt runs for performance and resource efficiency
• Implement data freshness checks and anomaly detection using dbt tests DevOps & Version Control
• Manage code deployments using Git repositories with branching strategies and pull requests
• Implement CI/CD pipelines for automated testing and deployment of data pipelines
• Establish code review processes and maintain coding standards
• Automate dbt runs and orchestrate workflows using tools like Airflow or dbt Cloud
• Monitor pipeline performance and implement alerting mechanisms Snowflake Engineering
• Develop complex SQL queries, stored procedures, and user-defined functions
• Implement partitioning, clustering, and materialized views for query optimization
• Configure and optimize Snowflake warehouses for different workloads
• Implement data sharing, secure views, and access controls
• Monitor and troubleshoot Snowflake query performance and resource usage Required Qualifications Experience
• 7+ years of progressive experience in data engineering roles
• 3+ years of hands-on Snowflake development experience
• 2+ years of production experience with dbt (data build tool) - this is mandatory
• Proven experience with database technologies including: Microsoft Azure SQL, AWS RDS, Oracle, Teradata, Netezza, MS SQL Server, PostgreSQL
• Hands-on experience with ETL/ELT tools and services
• Strong background in DevOps practices and Git-based workflows Technical Skills Core Requirements:
• dbt Expertise (MANDATORY): Advanced proficiency in dbt including models, tests, macros, documentation, and deployment
• Strong SQL Skills: Expert-level SQL with complex queries, window functions, CTEs, performance optimization
• Python Experience: Strong Python programming for data processing, automation, and pipeline development
• Git Proficiency: Experience with Git repositories, branching strategies, merge conflicts, and code reviews Snowflake Skills:
• Deep understanding of Snowflake architecture and best practices
• Experience with Snowpipe, streams, tasks, and stored procedures
• Knowledge of query optimization and warehouse configuration
• Understanding of Time Travel, Zero-Copy Cloning, and data sharing features DevOps & Engineering Practices:
• CI/CD pipeline deployment experience
• Test-driven development (TDD) and behavior-driven development (BDD) practices would be an advantage
• Infrastructure as Code experience (Terraform, CloudFormation)
• Container technologies (Docker, Kubernetes) knowledge
• Monitoring and logging tools experience ETL/ELT Tools & Services:
• Experience with modern ETL/ELT tools and cloud services
• Understanding of batch and streaming data processing patterns
• Familiarity with orchestration tools (Airflow, Prefect, Dagster)
• Knowledge of data integration patterns and best practices Cloud Platform Experience:
• AWS services: S3, Lambda, Glue, Kinesis, RDS
• Azure services: Data Factory, Databricks, Synapse Analytics
• Understanding of cloud security and networking concepts Preferred Qualifications
• Snowflake certifications (SnowPro Core, SnowPro Advanced Data Engineer)
• Experience with dbt Cloud or dbt Core in production environments
• Knowledge of data mesh or data fabric architectures
• Experience with real-time data streaming (Kafka, Kinesis)
• Familiarity with data quality frameworks and data observability tools
• Experience with BI tools integration (Tableau, Power BI, Looker)
• Background in agile/scrum methodologies Key Competencies
• Engineering Excellence: Strong commitment to code quality, testing, and documentation
• Problem-Solving: Ability to troubleshoot complex data pipeline issues and optimize performance
• Collaboration: Works effectively with cross-functional teams including data scientists, analysts, and business stakeholders
• Continuous Improvement: Proactively identifies opportunities for optimization and automation
• Communication: Clear documentation skills and ability to explain technical concepts
• Ownership Mentality: Takes responsibility for end-to-end delivery of data solutions Key Technology Responsibilities dbt Specific Responsibilities
• Develop staging, intermediate, and mart models following medallion architecture
• Write generic tests, singular tests, and custom test macros
• Configure incremental strategies and implement idempotent transformations
• Create snapshots for slowly changing dimensions (SCD Type 2)
• Implement data contracts and schema evolution strategies Git & DevOps Responsibilities
• Manage feature branches and conduct thorough code reviews
• Implement pre-commit hooks and automated testing
• Configure GitHub Actions or GitLab CI for automated deployments
• Maintain environment-specific configurations and secrets management
• Document deployment procedures and rollback strategies What We Offer
• Opportunity to work with cutting-edge data technologies and modern engineering practices
• Exposure to large-scale data challenges and cloud-native architectures
• Competitive compensation package aligned with experience
• Professional development opportunities including certifications and training
• Collaborative, engineering-focused culture
• [Add your specific benefits, location, remote work policy, and other perks] Application Requirements To apply, please submit:
• Resume highlighting your dbt, Snowflake, and DevOps experience
• Cover letter describing a complex data pipeline you've optimized
• GitHub profile or code samples demonstrating dbt and SQL expertise (preferred)
• Brief description of your experience with test-driven development in data engineering