Job Title: AWS Data Architect
10–15 Years, Locals Preferred
Last round Face to face, Alameda or Santa Clara
Primary (Must-Have) Skills
13+ 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, AWS Glue, Redshift, Athena, Lambda, EMR, Lake Formation, Kinesis, and RDS with a strong understanding of cloud-native data patterns & SQL development and advanced data modeling.
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 a 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, alongside experience in CI/CD.
Job Description & Responsibilities (RNR)
Design and define enterprise-level data architecture across AWS data platforms, ensuring scalability, security, performance, and alignment with business strategy.
Architect, develop, and oversee the 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.
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. [1]
Soft Skills & Other Skills
Communication Skill
Communicate effectively with internal and customer stakeholders.
Communication approach: verbal, emails, and instant messages.
Interpersonal Skills
Collaborative mindset; comfortable working across delivery, product, and sales functions.
Ability to distill 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
Task / Work Updates
Secondary Skills (Post-Hiring / Training Plan)
Experience with real-time streaming tools (Kafka, Kinesis).
Knowledge of data governance and compliance standards.
Prior experience in US-based client-facing roles.
Expected Outcome
We are seeking a highly skilled AWS Data Architect with strong 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.
