Data Architect (Snowflake)
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Role details
Tech stack
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Job description
Snowflake Architect (12-15 years): Lead the architecture, design and delivery of secure, scalable cloud data platforms on Snowflake. Define target-state architecture, data models, ingestion and ELT patterns, integration standards, governance, security and performance strategy. Translate business and analytics requirements into reliable technical solutions and provide hands-on technical leadership across delivery teams. .
Roles and responsibilities:
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Own end-to-end Snowflake solution architecture, including databases, schemas, warehouses, resource monitors, data sharing and environment strategy.
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Design dimensional and Data Vault models, batch/streaming pipelines and integrations using Snowpipe, Streams, Tasks, Dynamic Tables, APIs and leading ETL/ELT tools.
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Establish RBAC, masking, row-access policies, encryption, auditing, data retention and compliance controls.
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Optimize SQL, clustering, warehouse sizing, concurrency, caching and cost through monitoring and FinOps practices.
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Define CI/CD, infrastructure-as-code, testing, observability, backup, disaster recovery and release standards.
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Guide migrations from legacy/on-premises platforms to Snowflake, including assessment, planning, reconciliation and cutover.
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Lead architecture reviews, create HLD/LLD and standards, resolve complex issues, mentor engineers and coordinate with client, product, security and cloud teams.
Requirements
- Evaluate new Snowflake capabilities and GenAI/AI integration opportunities while ensuring production readiness. Required expertise: Advanced Snowflake architecture and administration, SQL, data warehousing, cloud services (AWS/Azure/Google Cloud Platform), ETL/ELT, Python, performance tuning, security/governance and stakeholder management. Strong communication, estimation and client-facing leadership skills are essential; SnowPro Advanced Architect certification is preferred.
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