Data Architect - Talent Pipeline

- Define current-state and target-state architectures across data ingestion, transformation, storage, orchestration, governance, security, and consumption. - Lead inventories and assessments of Python-, SQL-, and stored-procedure-based pipelines, classifying workloads by business criticality, frequency, volume, runtime, reliability, and cost. - Analyze Snowflake usage telemetry to establish cost and performance baselines across pipelines, warehouses, and workloads.

- Hands-on experience with Snowflake capabilities including Snowpark, Dynamic Tables, Streams and Tasks, stored procedures, and system usage views. - Expert-level SQL and strong Python skills. - Strong experience with dbt and data pipeline or orchestration technologies such as Fivetran, Kafka, Airflow, or similar tools.

- Establish architectural standards for security, access control, data governance, lineage, observability, performance, resilience, and business continuity. - Design data lakehouse and real-time data-processing architectures across AWS, Azure, or GCP. - Evaluate and recommend appropriate use of Snowflake Iceberg Tables and other open data architecture patterns.

- Strong understanding of data governance, access control, lineage, data quality, and metadata management. - Experience with at least one major cloud platform: AWS, Azure, or GCP. - Proven ability to lead discovery, assessment, architecture, and modernization engagements.

- Identify architectural and engineering anti-patterns, including procedural row-by-row processing, unnecessary full refreshes, missing incremental patterns, redundant transformations, warehouse mis-sizing, and insufficient workload isolation. - Recommend modernization strategies using set-based processing, incremental data patterns, Dynamic Tables, Streams and Tasks, Snowpark, dbt, and appropriate orchestration technologies. - Design scalable data models, governed data domains, semantic layers, and context models that support analytics and AI use cases.

- Expert-level SQL and strong Python skills. - Strong experience with dbt and data pipeline or orchestration technologies such as Fivetran, Kafka, Airflow, or similar tools. - Experience designing batch, streaming, lakehouse, and cloud-native data architectures.

- Design data lakehouse and real-time data-processing architectures across AWS, Azure, or GCP. - Evaluate and recommend appropriate use of Snowflake Iceberg Tables and other open data architecture patterns. - Build prioritized optimization backlogs and sequenced delivery roadmaps based on business impact, technical risk, cost, performance, and implementation effort.

- Experience building governed semantic or context layers for AI and LLM-based applications. - Experience with Snowflake Iceberg Tables and open lakehouse architectures. - Familiarity with Terraform, CI/CD, and infrastructure-as-code practices.

BlueCloud is a Snowflake Elite Partner and the 2026 CoCo Catalyst Snowflake Partner of the Year. We help enterprise organizations move from fragmented legacy systems to unified, AI-ready Snowflake platforms — delivering data migration, engineering, governance, BI & analytics, and AI/ML solutions 40–50% faster than traditional approaches. With 450+ Snowflake consultants, 200+ enterprise transformations under our belt, and a 100% Snowflake focus, we combine advisory-led thinking with AI-powered accelerators to turn months of work into weeks of results. Our clients span Financial Services, Healthcare & Life Sciences, Retail, Manufacturing, Energy, and more — and the outcomes speak for themselves: 97% faster reports, 40% fraud reduction, $1.5M in client savings, and 10× client growth.

BlueCloud is a Snowflake Elite Partner and the 2026 CoCo Catalyst Snowflake Partner of the Year. We help enterprise organizations move from fragmented legacy systems to unified, AI-ready Snowflake platforms — delivering data migration, engineering, governance, BI & analytics, and AI/ML solutions 40–50% faster than traditional approaches. With 450+ Snowflake consultants, 200+ enterprise transformations under our belt, and a 100% Snowflake focus, we combine advisory-led thinking with AI-powered accelerators to turn months of work into weeks of results. Our clients span Financial Services, Healthcare & Life Sciences, Retail, Manufacturing, Energy, and more — and the outcomes speak for themselves: 97% faster reports, 40% fraud reduction, $1.5M in client savings, and 10× client growth. We don't just strategize — we execute.

About the Role BlueCloud is seeking an experienced Data Architect to lead the assessment, design, and modernization of enterprise data platforms, with a strong focus on Snowflake. This role combines architecture leadership, hands-on platform expertise, and direct client engagement. You will define target-state architectures, assess existing data estates, establish modernization roadmaps, and guide multidisciplinary delivery teams through implementation. You will also help clients create secure, governed, cost-efficient, and AI-ready data platforms that support both current analytics requirements and future AI and context-layer initiatives.

Key Responsibilities - Lead the architecture, assessment, and modernization of enterprise Snowflake data platforms. - Define current-state and target-state architectures across data ingestion, transformation, storage, orchestration, governance, security, and consumption.

- Lead inventories and assessments of Python-, SQL-, and stored-procedure-based pipelines, classifying workloads by business criticality, frequency, volume, runtime, reliability, and cost. - Analyze Snowflake usage telemetry to establish cost and performance baselines across pipelines, warehouses, and workloads. - Identify architectural and engineering anti-patterns, including procedural row-by-row processing, unnecessary full refreshes, missing incremental patterns, redundant transformations, warehouse mis-sizing, and insufficient workload isolation.

- Design scalable data models, governed data domains, semantic layers, and context models that support analytics and AI use cases. - Architect Snowflake Cortex solutions using capabilities such as Cortex Analyst, Cortex Search, and Cortex LLM functions. - Establish architectural standards for security, access control, data governance, lineage, observability, performance, resilience, and business continuity.

- 10+ years of experience in data architecture, data engineering, or a comparable senior technical role. - At least 2–4 years of deep Snowflake architecture and implementation experience. - Proven experience designing and modernizing enterprise-scale Snowflake data platforms.

- At least 2–4 years of deep Snowflake architecture and implementation experience. - Proven experience designing and modernizing enterprise-scale Snowflake data platforms. - Strong knowledge of Snowflake environment design, security, governance, data modeling, workload management, and performance and cost optimization.

- Proven experience designing and modernizing enterprise-scale Snowflake data platforms. - Strong knowledge of Snowflake environment design, security, governance, data modeling, workload management, and performance and cost optimization. - Hands-on experience with Snowflake capabilities including Snowpark, Dynamic Tables, Streams and Tasks, stored procedures, and system usage views.

- Strong knowledge of Snowflake environment design, security, governance, data modeling, workload management, and performance and cost optimization. - Hands-on experience with Snowflake capabilities including Snowpark, Dynamic Tables, Streams and Tasks, stored procedures, and system usage views. - Expert-level SQL and strong Python skills.

Preferred Qualifications - Hands-on experience with Snowflake Cortex, including Cortex Analyst, Cortex Search, or Cortex LLM functions. - Experience building governed semantic or context layers for AI and LLM-based applications.

- Familiarity with Terraform, CI/CD, and infrastructure-as-code practices. - Experience with FinOps, cloud cost governance, and Snowflake consumption optimization. - Experience designing business continuity and disaster recovery solutions.

- Experience with Snowflake Iceberg Tables and open lakehouse architectures. - Familiarity with Terraform, CI/CD, and infrastructure-as-code practices. - Experience with FinOps, cloud cost governance, and Snowflake consumption optimization.