Mphasis
Senior Snowflake Data Engineer
United Kingdom
Posted about 15 hours ago
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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
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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
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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
We are an Equal Opportunity Employer committed to building a diverse and inclusive team.
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