Data Architect - Talent Pipeline at Blue — Remote, USA | Base Career

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.

The ideal candidate is a trusted technical advisor who can translate complex business requirements into practical architecture solutions and communicate effectively with engineering teams, business stakeholders, and executive sponsors.

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.

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.

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.
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.
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.
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.
Provide technical leadership across multiple concurrent projects and guide engineers, analysts, QA specialists, and DevOps teams.
Support project planning, estimation, scope definition, dependency management, risk mitigation, and technical governance.
Lead discovery workshops and interviews with client stakeholders and subject-matter experts.
Present architecture decisions, assessment findings, quantified impact projections, and roadmap recommendations to technical and executive audiences.
Act as a trusted advisor to clients throughout architecture and delivery engagements.
Create and maintain architecture diagrams, decision records, technical standards, and platform documentation.

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.
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.
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.
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.
Experience providing technical leadership across multidisciplinary Agile delivery teams.
Strong client-facing, presentation, and stakeholder-management skills.
Ability to communicate complex technical concepts clearly to engineering teams, business leaders, and executive sponsors.

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.
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.
Experience designing business continuity and disaster recovery solutions.
SnowPro Advanced: Architect or SnowPro Core certification.
Consulting or enterprise client-delivery experience.
Experience acting as a technical delivery lead or Scrum Master when required.
Familiarity with Jira, Confluence, and architecture tools such as Lucidchart.

Data Architect - Talent Pipeline

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