Snowflakes Data Engineer

Roles & Responsibilities

Key Responsibilities

• Design, build, and operate end-to-end data pipelines (ingestion → transformation → serving) on Databricks and/or Snowflake, following medallion/layered architecture patterns
• Configure and administer workspaces/accounts — compute policies, resource sizing, environment setup, and access hierarchy — per the SDP reference architecture
• Implement data governance controls: catalogue and schema design, RBAC, row/column-level security, data masking, and lineage tracking
• Set up CI/CD and infrastructure-as-code for pipeline deployment and environment promotion (dev → test → prod)
• Configure monitoring, telemetry, and audit logging to meet SDP's central observability and security posture requirements
• Support UAT, integration testing, and parallel-run validation during migration and go-live
• Produce handover documentation (runbooks, access lists, escalation procedures) for agency operations teams
• Work directly with client, agency stakeholders, and Principal (Databricks/Snowflake) solution architects throughout delivery

Required Technical Skills — Snowflake

• Virtual warehouse sizing, scaling, and cost/performance tuning
• Snowpipe and Snowpipe Streaming for continuous ingestion
• Snowpark (Python/Scala) for in-warehouse data engineering
• Role-based access control (RBAC), secure data sharing, and object tagging for governance
• Query profiling and performance optimization (clustering keys, materialized views, caching)
• Time Travel, zero-copy cloning, and Snowflake's native data protection features
• Minimum 5 years of hands-on experience in Data Engineering, Data Platform Engineering, or related disciplines.
• Minimum 3 years of hands-on experience with Snowflakes involving data pipeline

Required Technical Skills — Common

• Strong SQL and Python (PySpark or general-purpose) for data engineering
• Data modeling — dimensional design, star/snowflake schemas, semantic layers
• CI/CD pipelines (e.g., Azure DevOps, GitHub Actions, GitLab CI) for data engineering workflows
• Infrastructure-as-code (Terraform preferred) for provisioning cloud data platform resources
• Hands-on experience on at least one hyperscaler — AWS, Azure, or Google Cloud
• Understanding of data security and compliance frameworks applicable to government/public-sector environments

Preferred Qualifications

• Databricks Certified Data Engineer Associate/Professional
• SnowPro Core, or SnowPro Advanced: Data Engineer
• Prior experience delivering on a government or regulated-sector data platform, or exposure to compliance frameworks such as IM8 is an add on
• Experience working as part of a System Integrator (SI) delivery team alongside a platform Principal is an add on

Tell employers what skills you have

Large Systems Integration
Design
Group Policies
Solution Delivery
Uat Support
Data Pipeline
Compliance Solutions
Infrastructure Deployment
Data Engineering
Telemetry
Data Masking
Integration Testing
Operational Technology Security Audit Management
RBAC
Agency Management
Migration Testing