Scope:
- The role requires both hands-on advanced engineering and architectural leadership, ensuring performant, secure, and future-ready data ecosystems across major business units.
- The individual will own end-to-end data architecture, multi-cluster compute scaling, and technical governance across Snowflake features (Iceberg, Snowpark, native governance).
- The position involves enabling FinOps optimization, architectural innovation, and platform automation while guiding cross-functional stakeholders and engineering teams.
Technical Environment:
- Snowflake Platform: Multi-Cluster Warehouses, Snowpipe, Tasks, Streams, Zero-Copy Cloning, Time Travel, Apache Iceberg tables.
- Data Engineering & Scripting: Advanced SQL, Python (Snowpark), Java/Scala (UDFs/UDTFs), dbt (Data Build Tool).
- Integrations & Orchestration: Apache Airflow, Fivetran, Kafka, Spark, Trino, external catalogs (AWS Glue, Polaris).
- Governance & Security: Hierarchical RBAC, Dynamic Data Masking, Row Access Policies, Object Tagging, Secure Data Sharing.
- Platform Enhancements: Snowpark Container Services, Snowflake Cortex (AI/ML), Search Optimization Service, Materialized Views.
- DataOps/Agile: CI/CD pipelines, Git, GitHub Actions/GitLab, Terraform (Infrastructure-as-Code), Agile delivery.
What you'll do:
- Design & Architect: Define scalable, petabyte-scale data lakehouse architectures. Establish enterprise coding standards, hierarchical RBAC models, and data security best practices.
- Develop & Deliver: Architect multi-cluster compute topologies for high-concurrency workloads. Build low-latency integrations with external compute engines and catalogs.
- Guide & Govern: Provide technical leadership to data engineers. Lead technical whiteboarding sessions and data strategy workshops with business stakeholders.
- Operate & Optimize: Implement robust FinOps monitoring, compute quotas, and warehouse right-sizing routines. Perform deep root-cause analysis on chronic platform contention issues.
What we are looking for:
- Bachelor's degree in Computer Science, Data Engineering, IT, or a related technical field.
- 9-12 years of IT/Data experience, with 5-7+ years specifically in deep Snowflake implementation, architecture, and system design.
- Proven experience designing modern data stacks utilizing open table formats (Apache Iceberg) and Data Mesh principles.
- Experience in FinOps (resource monitors, chargeback models) and enterprise security (Dynamic Data Masking, Row Access Policies).
- Strong communication and stakeholder management skills to influence technical roadmaps.
- Snowflake Certifications - SnowPro Advanced (Architect or Data Engineer) strongly preferred.
Our Values
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All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.