Title:- AWS Data Architect
Location Clinton, New Jersey
Work Mode Hybrid – 3 days a week from office
Employment Type:- Full-time
Role Overview
We are seeking a highly experienced and hands-on AWS Data Architect to lead the design, implementation, and governance of enterprise-scale data platforms on AWS. This role requires deep technical expertise, strong architectural ownership, and the ability to actively contribute to development while guiding teams.
The ideal candidate will be a player-coach—capable of defining architecture, building solutions, and ensuring best practices across data engineering, analytics, and governance.
Key Responsibilities
Architecture & Design
Define and own end-to-end data architecture on AWS (ingestion, storage, transformation, consumption)
Design scalable, secure, and high-performing data platforms (lakehouse / modern data stack)
Establish standards for data modeling, partitioning, metadata, and lifecycle management
Architect solutions for both batch and real-time data processing
Hands-On Engineering
Build and implement pipelines using AWS Glue, EMR, Lambda, Step Functions
Design data storage using S3, Redshift, RDS, DynamoDB
Develop and optimize ETL/ELT pipelines using PySpark, SQL, and Python
Implement data transformation frameworks and reusable components
Data Governance & Security
Define and enforce data governance, cataloging, and lineage
Design row-level security, IAM policies, encryption strategies
Work with AWS Lake Formation / Glue Data Catalog
Performance & Optimization
Optimize data pipelines for performance and cost efficiency
Drive SPICE/BI dataset optimization (if QuickSight or similar tools involved)
Improve query performance in Redshift/S3-based architectures
Collaboration & Leadership
Work closely with business, analytics, and engineering teams
Lead technical discussions and design reviews
Mentor data engineers and enforce engineering best practices
Act as the primary owner of data architecture decisions
Migration & Modernization
Lead legacy data platform migrations (e.g., on-prem, Tableau, Hadoop) to AWS
Define strategies for data platform modernization and cloud-native adoption
Support large-scale BI/reporting migrations (e.g., to QuickSight)
Reporting Frameworks & Reusable Components
Create reusable reporting templates, dataset templates, and QuickSight themes.
Build standardized KPIs, calculated fields, and metric definitions.
Design modular AI agents and workflow templates that can be used across multiple business functions.
Design modular reporting components that can be used across multiple dashboards.
Implement parameterized dashboards and reusable visual components.
Quick Suite Development & AI-Powered Reporting
Design, develop, and maintain interactive dashboards, datasets, and visualizations in Amazon QuickSight (now part of Quick Suite).
Build and configure Quick Chat agents to enable natural language querying across business data sources.
Design Quick Spaces that group data, applications, and AI agents for specific business functions or teams.
Build high-performance dashboards optimized for large datasets and fast refresh times.
Implement row-level security (RLS) and governance controls for business users and AI agents.
Create standardized QuickSight templates and dashboard frameworks that can be reused across teams.
Design and maintain semantic layers and curated datasets for reporting and AI consumption.
Ideal Candidate Profile
Overall 12+ years of experience, including 5 to 7+ years in AWS Data Architecture.
Core AWS Expertise
Deep experience with:
S3 (data lake design)
AWS Glue (ETL, catalog)
Amazon Redshift (data warehouse design & optimization)
Lambda, Step Functions (orchestration)
IAM, Lake Formation (security)
Data Engineering & Processing
Strong hands-on experience with:
PySpark / Spark (EMR or Glue)
SQL (advanced level)
Python for data pipelines
Experience with streaming (Kinesis / Kafka) is a plus
Data Architecture
Expertise in:
Data lake / lakehouse architectures
Data modeling (dimensional + normalized)
Metadata and cataloging strategies
Handling large-scale, distributed data systems
Modern Data Stack (Preferred)
Exposure to:
dbt, Airflow, Snowflake (optional but valuable)
BI tools (QuickSight, Tableau, Power BI)
API-based ingestion and microservices-based data flows
Amazon Quick Suite (QuickSight, Quick Chat, Quick Flows, Quick Automate, Quick Research)
SQL & Data Modeling
AWS Analytics Stack
Dashboard Design
AI Agent Design & Configuration
Workflow Automation & Business Process Optimization
Soft Skills
Strong ownership mindset and ability to drive architecture end-to-end
Excellent communication with both technical and business stakeholders
Ability to work in fast-paced, ambiguous environments
Proven leadership and mentoring experience
Nice-to-Have
AWS Certifications (Solutions Architect, Data Analytics Specialty)
Experience with data governance frameworks / regulatory compliance
Background in large enterprise transformations
Education
Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent experience
