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Data Architect (AWS)

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Onsite

Data Architect (AWS)

BrezQ

Data Architect (AWS)

Skills

Data EngineeringTableauKafkaData AnalysisAWSCRMSalesforceCompliance

8 days ago

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Important information


Contract type:

Permanent

Location:

Alameda, CA, USA

Work mode:

Onsite

Published on:

15 October 2026

What they need


We’re Hiring: AWS Data Architect / Technical Architect

Location: Alameda, CA (Hybrid – 4 days onsite)

Role Type: Full-Time (Preferred)

About the Role

We are seeking an experienced AWS Data Architect to lead the design, development, and maintenance of scalable data pipelines and modern analytics solutions. In this role, you will work closely with business stakeholders, data engineers, and CRM teams to enable seamless data integration, automated reporting, and enterprise-grade insights.

What We’re Looking For

  • 12+ Years in overall IT, with 7+ years dedicated to Data Engineering & Analytics.
  • 5+ Years of hands-on AWS Data Architecture experience ( S3, Glue, Redshift, Lambda, EMR, Lake Formation, RDS ).
  • 3+ Years in a Lead / Technical Architect capacity guiding teams and setting architectural standards.
  • 3+ Years designing real-time and batch processing data pipelines with CI/CD integration.
  • Hands-on expertise with Salesforce integrations and Tableau visualization .
  • Strong knowledge of data governance, compliance standards , and client-facing communication.

Key Responsibilities

  • Architect & Design: Lead end-to-end cloud-native data architecture, enterprise data platform implementation, and data modeling strategies.
  • Pipeline Engineering: Design and build resilient batch and real-time streaming architectures (Kafka, Kinesis).
  • Cross-Functional Integration: Integrate CRM systems (Salesforce Sales/Service Cloud) with external data platforms using APIs, middleware, and native connectors.
  • Technical Leadership: Guide data engineering teams, establish design standards, conduct code reviews, and mentor engineers.
  • Analytics & Visualization: Oversee Tableau dashboard development, data modeling, visual reporting best practices, and performance tuning.

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