Jobs via Dice
Title:
Data Architect (Azure & Google Cloud Platform)
Location:
Issaquah, WA (Onsite)
Client:
Amaze Systems Inc (End Client: UST Global //COSTCO)
Role Overview:
As a Data Architect specializing in Microsoft Azure and Google Cloud Platform (Google Cloud Platform), you will be responsible for designing, implementing, and optimizing enterprise‑grade data architectures that enable advanced analytics, AI/ML, and business intelligence across multi‑cloud environments. This role requires deep expertise in data engineering, data modeling, cloud‑native architecture, and governance to support scalable, secure, and high‑performance data ecosystems.
Key Responsibilities:
Architect and Design: Define end‑to‑end data architecture strategies, including ingestion, storage, processing, and consumption layers leveraging Azure Synapse Analytics, Azure Data Factory, Databricks, BigQuery, Dataflow, and Pub/Sub. Cloud Data Integration: Design and build hybrid and multi‑cloud data solutions integrating structured, semi‑structured, and unstructured data sources across Azure and Google Cloud Platform. Data Modeling: Develop conceptual, logical, and physical data models supporting data warehouses, data lakes, and lakehouse architectures. ETL/ELT Pipelines: Lead the design and implementation of data pipelines using ADF, Synapse Pipelines, Google Cloud Platform Dataflow, and Cloud Composer, ensuring scalability and maintainability. Analytics & BI Enablement: Support data consumption through Power BI, Looker, or Tableau, enabling advanced analytics and machine learning initiatives. Data Governance & Security: Implement data governance frameworks, metadata management, lineage, and compliance with GDPR, HIPAA, or SOX using tools like Purview and Data Catalog. Performance Optimization: Optimize data pipelines, queries, and storage performance across Azure Data Lake Storage (ADLS), BigQuery, and Cloud Storage. Collaboration: Partner with data engineers, analysts, and business stakeholders to translate business requirements into scalable data architecture solutions. Infrastructure as Code (IaC): Utilize Terraform, ARM templates, and Deployment Manager for automating data infrastructure deployment. Innovation & Best Practices: Drive adoption of data mesh, data fabric, and Lakehouse paradigms to modernize enterprise data landscapes.
Technical Skills:
Cloud Platforms: Azure (Synapse, Data Factory, Databricks, ADLS, Purview), Google Cloud Platform (BigQuery, Dataflow, Pub/Sub, Cloud Storage, Dataproc, Composer). Data Engineering: SQL, Python, PySpark, Airflow, Kafka, Beam. Data Modeling Tools: ER/Studio, Power Designer, dbt, or similar. Data Governance: Azure Purview, Google Data Catalog, Collibra, Alation. DevOps & IaC: Terraform, GitHub Actions, Jenkins, Azure DevOps. Databases: SQL Server, PostgreSQL, Cosmos DB, Spanner, Firestore. Visualization: Power BI, Looker, Tableau.
Preferred Qualifications:
Bachelor's or Master’s in Computer Science, Data Engineering, or a related field. 8-15 years of experience in data architecture and engineering. Certifications: Microsoft Certified: Azure Data Engineer/Architect, Google Professional Data Engineer/Architect. Experience working with multi‑cloud and hybrid data ecosystems. Strong understanding of data governance, lineage, and privacy frameworks.
Seniority level:
Mid‑Senior level
Employment type:
Full‑time
Job function:
Engineering and Information Technology
Industries:
Software Development
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Data Architect (Azure & Google Cloud Platform)
Location:
Issaquah, WA (Onsite)
Client:
Amaze Systems Inc (End Client: UST Global //COSTCO)
Role Overview:
As a Data Architect specializing in Microsoft Azure and Google Cloud Platform (Google Cloud Platform), you will be responsible for designing, implementing, and optimizing enterprise‑grade data architectures that enable advanced analytics, AI/ML, and business intelligence across multi‑cloud environments. This role requires deep expertise in data engineering, data modeling, cloud‑native architecture, and governance to support scalable, secure, and high‑performance data ecosystems.
Key Responsibilities:
Architect and Design: Define end‑to‑end data architecture strategies, including ingestion, storage, processing, and consumption layers leveraging Azure Synapse Analytics, Azure Data Factory, Databricks, BigQuery, Dataflow, and Pub/Sub. Cloud Data Integration: Design and build hybrid and multi‑cloud data solutions integrating structured, semi‑structured, and unstructured data sources across Azure and Google Cloud Platform. Data Modeling: Develop conceptual, logical, and physical data models supporting data warehouses, data lakes, and lakehouse architectures. ETL/ELT Pipelines: Lead the design and implementation of data pipelines using ADF, Synapse Pipelines, Google Cloud Platform Dataflow, and Cloud Composer, ensuring scalability and maintainability. Analytics & BI Enablement: Support data consumption through Power BI, Looker, or Tableau, enabling advanced analytics and machine learning initiatives. Data Governance & Security: Implement data governance frameworks, metadata management, lineage, and compliance with GDPR, HIPAA, or SOX using tools like Purview and Data Catalog. Performance Optimization: Optimize data pipelines, queries, and storage performance across Azure Data Lake Storage (ADLS), BigQuery, and Cloud Storage. Collaboration: Partner with data engineers, analysts, and business stakeholders to translate business requirements into scalable data architecture solutions. Infrastructure as Code (IaC): Utilize Terraform, ARM templates, and Deployment Manager for automating data infrastructure deployment. Innovation & Best Practices: Drive adoption of data mesh, data fabric, and Lakehouse paradigms to modernize enterprise data landscapes.
Technical Skills:
Cloud Platforms: Azure (Synapse, Data Factory, Databricks, ADLS, Purview), Google Cloud Platform (BigQuery, Dataflow, Pub/Sub, Cloud Storage, Dataproc, Composer). Data Engineering: SQL, Python, PySpark, Airflow, Kafka, Beam. Data Modeling Tools: ER/Studio, Power Designer, dbt, or similar. Data Governance: Azure Purview, Google Data Catalog, Collibra, Alation. DevOps & IaC: Terraform, GitHub Actions, Jenkins, Azure DevOps. Databases: SQL Server, PostgreSQL, Cosmos DB, Spanner, Firestore. Visualization: Power BI, Looker, Tableau.
Preferred Qualifications:
Bachelor's or Master’s in Computer Science, Data Engineering, or a related field. 8-15 years of experience in data architecture and engineering. Certifications: Microsoft Certified: Azure Data Engineer/Architect, Google Professional Data Engineer/Architect. Experience working with multi‑cloud and hybrid data ecosystems. Strong understanding of data governance, lineage, and privacy frameworks.
Seniority level:
Mid‑Senior level
Employment type:
Full‑time
Job function:
Engineering and Information Technology
Industries:
Software Development
#J-18808-Ljbffr