Data Architect

🕒 il y a 8 jours

🇺🇸 États-Unis – Télétravail

⏰ Temps Plein

🟠 Senior

🔴 Expert

🚰 Ingénieur Data

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BlueCloud

Site WebLinkedInTous les Emplois

501 - 1000 employés

Fondée en 2004

💼 Conseil

📣 Marketing

📦 Logistique

Consulting • Marketing • Logistics

BlueCloud est une entreprise technologique mondiale spécialisée dans la transformation des entreprises par le biais des données, de l'analytique et de l'IA générative. Ses services comprennent l'ingénierie des données, l'analytique, la conception de logiciels, le DevOps et la gouvernance des données, en s'appuyant sur une technologie d'IA révolutionnaire pour améliorer la prise de décision et l'efficacité. En tant que partenaire de croissance reconnu des services de données en cloud, BlueCloud propose des solutions cloud de bout en bout qui permettent aux organisations de maximiser leur potentiel de données et de soutenir la transformation numérique grâce à des équipes mondiales évolutives et performantes.

Description

• 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.

🎯 Exigences

• 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.