Senior Snowflake Data Engineer

Senior Snowflake Data EngineerPosition OverviewWe 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 ResponsibilitiesData Pipeline Development & OptimizationDesign, develop, and optimize high-performance data pipelines in SnowflakeImplement and maintain dbt models with comprehensive testing and documentationApply test-driven development patterns using dbt tests, including data quality checks and schema testsOptimize existing pipelines to reduce processing time and Snowflake compute costsBuild incremental models and implement efficient data loading strategiesCreate and maintain data transformation workflows using SQL and Pythondbt Development & TestingBuild modular, reusable dbt models following best practices and style guidesImplement comprehensive testing strategies including unit tests, data tests, and schema testsCreate and maintain dbt documentation for data lineage and business logicDevelop custom dbt macros for reusable transformations and testing patternsConfigure and optimize dbt runs for performance and resource efficiencyImplement data freshness checks and anomaly detection using dbt testsDevOps & Version ControlManage code deployments using Git repositories with branching strategies and pull requestsImplement CI/CD pipelines for automated testing and deployment of data pipelinesEstablish code review processes and maintain coding standardsAutomate dbt runs and orchestrate workflows using tools like Airflow or dbt CloudMonitor pipeline performance and implement alerting mechanismsSnowflake EngineeringDevelop complex SQL queries, stored procedures, and user-defined functionsImplement partitioning, clustering, and materialized views for query optimizationConfigure and optimize Snowflake warehouses for different workloadsImplement data sharing, secure views, and access controlsMonitor and troubleshoot Snowflake query performance and resource usageRequired QualificationsExperience7+ years of progressive experience in data engineering roles3+ years of hands-on Snowflake development experience2+ years of production experience with dbt (data build tool) - this is mandatoryProven experience with database technologies including: Microsoft Azure SQL, AWS RDS, Oracle, Teradata, Netezza, MS SQL Server, PostgreSQLHands-on experience with ETL/ELT tools and servicesStrong background in DevOps practices and Git-based workflowsTechnical SkillsCore Requirements:dbt Expertise (MANDATORY): Advanced proficiency in dbt including models, tests, macros, documentation, and deploymentStrong SQL Skills: Expert-level SQL with complex queries, window functions, CTEs, performance optimizationPython Experience: Strong Python programming for data processing, automation, and pipeline developmentGit Proficiency: Experience with Git repositories, branching strategies, merge conflicts, and code reviewsSnowflake Skills:Deep understanding of Snowflake architecture and best practicesExperience with Snowpipe, streams, tasks, and stored proceduresKnowledge of query optimization and warehouse configurationUnderstanding of Time Travel, Zero-Copy Cloning, and data sharing featuresDevOps & Engineering Practices:CI/CD pipeline deployment experienceTest-driven development (TDD) and behavior-driven development (BDD) practices would be an advantageInfrastructure as Code experience (Terraform, CloudFormation)Container technologies (Docker, Kubernetes) knowledgeMonitoring and logging tools experienceETL/ELT Tools & Services:Experience with modern ETL/ELT tools and cloud servicesUnderstanding of batch and streaming data processing patternsFamiliarity with orchestration tools (Airflow, Prefect, Dagster)Knowledge of data integration patterns and best practicesCloud Platform Experience:AWS services: S3, Lambda, Glue, Kinesis, RDSAzure services: Data Factory, Databricks, Synapse AnalyticsUnderstanding of cloud security and networking conceptsPreferred QualificationsSnowflake certifications (SnowPro Core, SnowPro Advanced Data Engineer)Experience with dbt Cloud or dbt Core in production environmentsKnowledge of data mesh or data fabric architecturesExperience with real-time data streaming (Kafka, Kinesis)Familiarity with data quality frameworks and data observability toolsExperience with BI tools integration (Tableau, Power BI, Looker)Background in agile/scrum methodologiesKey CompetenciesEngineering Excellence: Strong commitment to code quality, testing, and documentationProblem-Solving: Ability to troubleshoot complex data pipeline issues and optimize performanceCollaboration: Works effectively with cross-functional teams including data scientists, analysts, and business stakeholdersContinuous Improvement: Proactively identifies opportunities for optimization and automationCommunication: Clear documentation skills and ability to explain technical conceptsOwnership Mentality: Takes responsibility for end-to-end delivery of data solutionsKey Technology Responsibilitiesdbt Specific ResponsibilitiesDevelop staging, intermediate, and mart models following medallion architectureWrite generic tests, singular tests, and custom test macrosConfigure incremental strategies and implement idempotent transformationsCreate snapshots for slowly changing dimensions (SCD Type 2)Implement data contracts and schema evolution strategiesGit & DevOps ResponsibilitiesManage feature branches and conduct thorough code reviewsImplement pre-commit hooks and automated testingConfigure GitHub Actions or GitLab CI for automated deploymentsMaintain environment-specific configurations and secrets managementDocument deployment procedures and rollback strategiesWhat We OfferOpportunity to work with cutting-edge data technologies and modern engineering practicesExposure to large-scale data challenges and cloud-native architecturesCompetitive compensation package aligned with experienceProfessional development opportunities including certifications and trainingCollaborative, engineering-focused culture[Add your specific benefits, location, remote work policy, and other perks]Application RequirementsTo apply, please submit:Resume highlighting your dbt, Snowflake, and DevOps experienceCover letter describing a complex data pipeline you've optimizedGitHub profile or code samples demonstrating dbt and SQL expertise (preferred)Brief description of your experience with test-driven development in data engineeringWe are an Equal Opportunity Employer committed to building a diverse and inclusive team.