AWS Data Architect - Alameda, CA - Full Time

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Our client seeks an AWS Data Architect for a Full Time Project in Alameda, CA . Below is the detailed requirement

Job Title: AWS Data Architect

Work location : Alameda, CA

Duration: Full Time

We are seeking a highly skilled AWS Data Architect with experience in Salesforce and Tableau integration to design, develop, and maintain scalable data pipelines and analytics solutions. The ideal candidate will work closely with business stakeholders, data teams, and CRM teams to ensure seamless data flow, reporting, and insights generation.

Job Description:

• Bachelor's degree preferably in Computer Science, Information technology, Computer Engineering, or related IT discipline or equivalent experience with 15 Minimum Experience
• Minimum 10 years of overall IT experience, with 8 years in Data Engineering & Analytics, including end-to-end data solution design, architecture, and enterprise data platform implementation
• 6 years of hands-on experience in AWS data architecture, including Amazon S3, Glue, Redshift, Athena, Lambda, EMR, Lake Formation, Kinesis, and RDS with strong understanding of cloud-native data patterns, SQL development and advanced data modelling
• 3 years of experience in integrating Salesforce (Sales Cloud / Service Cloud) with external data platforms using APIs, connectors, and middleware tools
• 3 years of experience in leading data engineering teams as Technical Architect / Lead, providing architecture guidance, code reviews, design standards, and mentoring developers
• 4 years of hands-on experience with Tableau, including dashboard development, data modeling, performance tuning, and data visualization best practices
• 3 years of experience in real-time and batch data processing architectures, including streaming frameworks and large-scale data, ingestion and experience in CI/CD
• Experience with real-time streaming tools (Kafka, Kinesis); Knowledge of data governance and compliance standards; Prior experience in Client-facing roles
  
  

Job / Role Description

• Design and define enterprise-level data architecture across AWS data platforms, ensuring scalability, security, performance, and alignment with business strategy
• Architect, develop, and oversee implementation of data lakes/Lakehouse solutions using AWS services such as S3, Glue, Redshift, Athena, EMR, Lambda, and Lake Formation
• Lead the design and development of robust ETL/ELT pipelines (batch and real-time), ensuring high data quality, reliability, and performance optimization
• Integrate and synchronize data between Salesforce and AWS data platforms; Drive modernization initiatives including migration from legacy/on-prem systems to AWS Cloud environments
• Define and implement enterprise data models (conceptual, logical, physical), including dimensional modeling (Star/Snowflake schemas) to support analytics and reporting needs
• Establish BI architecture standards using Tableau, including semantic layer design, dashboard governance, security (row-level security), and performance optimization; Translate complex business requirements into scalable technical architecture and actionable data solutions
• Provide hands-on technical leadership in SQL, Python/PySpark, query optimization, and performance tuning for large-scale datasets; Define and enforce data governance, security frameworks (IAM, encryption, masking), and compliance standards across the data ecosystem.
• Guide teams in implementing CI/CD pipelines, Infrastructure as Code (Terraform/CloudFormation), and DevOps best practices for data platforms; Review solution designs and code to ensure adherence to architectural standards, scalability principles, and best practices
• Mentor and technically guide data engineers and BI developers, establishing development standards and reusable frameworks; Continuously evaluate emerging technologies, BI trends, and AWS innovations to recommend improvements and optimize enterprise data capabilities
• Collaborate with cross-functional teams to gather requirements and deliver scalable solutions; Ensure monitoring, logging, observability, backup, and disaster recovery strategies are implemented effectively
• Communicate effectively with internal and customer stakeholders; Communication approach: verbal, emails and instant messages; Ability to distil complex industry concepts into digestible insights for technical and non-technical audiences; Self-driven, organized, and adaptive in a fast-paced environment
• Problem-Solving and Analytical Thinking; Collaborative mindset; comfortable working across delivery, product, and sales functions; Prior experience in working on Agile/Scrum projects with exposure to tools like Jira
• Provides regular updates, proactive and due diligent to carry out responsibilities
• Capability to troubleshoot and resolve issues efficiently; Analytical mindset