Principal Data Engineer
First seen by Alion on Sep 16, 2026.
Principal Data Engineer Snowflake to lead the design, development, and delivery of enterprise-scale data solutions built on Snowflake.
This is a highly technical, hands-on principal-level role focused on Snowflake architecture, data engineering, data migration, data modeling, performance optimization, governance, and enterprise data platform development.
You will work across complex enterprise environments to design and implement scalable Snowflake solutions that support analytics, business intelligence, operational workloads, and increasingly AI/ML use cases.
The ideal candidate has deep, hands-on Snowflake experience combined with strong data engineering and architectural skills. You should be comfortable making technical architecture decisions, solving complex Snowflake problems, establishing engineering standards, and mentoring other engineers while remaining hands-on with implementation.
Key Responsibilities :
- Lead the architecture, design, and implementation of enterprise-grade Snowflake data platforms.
- Design scalable Snowflake architectures supporting enterprise analytics, BI, operational workloads, and AI/ML use cases.
- Develop complex ETL/ELT pipelines and data integration solutions using Snowflake and modern data engineering technologies.
- Design and implement robust data models, including dimensional, normalized, denormalized, and analytical data models.
- Perform Snowflake data migrations from legacy databases, data warehouses, and other platforms.
- Design and implement Snowflake solutions using Streams, Tasks, Stored Procedures, Dynamic Tables, Snowpipe, Snowpipe Streaming, and other Snowflake capabilities.
- Optimize Snowflake workloads for performance, scalability, reliability, and cost efficiency.
- Implement Snowflake security and governance, including RBAC, masking policies, row access policies, secure views, data classification, and access controls.
- Design solutions for data quality, data lineage, metadata management, and enterprise data governance.
- Develop and optimize complex SQL and Python-based data processing solutions.
- Work with Snowpark to develop scalable data engineering and data processing workloads where appropriate.
- Design integrations between Snowflake and APIs, applications, cloud services, streaming platforms, and other enterprise systems.
- Troubleshoot complex Snowflake performance, data quality, pipeline, and production issues.
- Establish reusable Snowflake engineering patterns, frameworks, coding standards, and best practices.
- Lead technical design sessions and make architecture decisions for complex data engineering initiatives.
- Review technical designs and code produced by other engineers and provide architectural and technical guidance.
- Mentor Senior Data Engineers and help raise engineering standards across the team.
- Work directly with Data Architects, Solution Architects, AI/ML Engineers, application teams, and client stakeholders.
- Translate business and architectural requirements into scalable, production-ready Snowflake solutions.
- Support technical discovery, estimation, solution design, and delivery planning for enterprise client engagements.
- Stay current with new Snowflake capabilities and identify opportunities to improve existing platforms and solutions.
Required Qualifications :
- 8 - 12 years of experience in data engineering, data architecture.
- Deep hands-on experience with Snowflake in enterprise production environments.
- Proven experience designing and implementing large-scale Snowflake data platforms and architectures.
- Strong expertise in Snowflake SQL and advanced SQL development.
- Strong Python development experience for data engineering and automation.
- Extensive experience designing and implementing ETL/ELT pipelines.
- Strong understanding of data warehousing and modern data architecture principles.
- Strong experience with data modeling, including dimensional modeling and enterprise data warehouse design.
- Hands-on experience with several Snowflake capabilities, including :
1. Snowflake Streams
2. Snowflake Tasks
3. Stored Procedures
4. Snowpipe / Snowpipe Streaming
5. Dynamic Tables
6. Time Travel
7. Zero-Copy Cloning
8. Secure Views
9. Materialized Views
10. Snowflake Resource Monitors
- Strong understanding of Snowflake performance optimization and cost optimization.
- Strong experience with Snowflake security, including :
1. RBAC
2. Role hierarchy
3. Row Access Policies
4. Masking Policies
5. Secure Views
6. Data classification
7. Access controls
- Experience with Snowflake data migration and modernization projects.
- Experience integrating Snowflake with cloud platforms, APIs, applications, and other enterprise data systems.
- Strong understanding of data quality, governance, lineage, and metadata management.
- Experience with Git, CI/CD, automated testing, and modern software engineering practices.
- Experience troubleshooting complex production data and Snowflake issues.
- Demonstrated ability to provide technical leadership and architectural guidance to other engineers.
- Excellent communication skills and the ability to work directly with technical and business stakeholders.
- Snowflake certification
Skills
Data Engineering, Snowflake DB, ETL, Data Pipeline, Data Warehousing, SQL, Python, Data Modeling, Dimensional Modeling