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AWS Data Architect

new york technology partnersClinton, NJ

today

Occupations

Database ArchitectsData Warehousing SpecialistsComputer Systems Engineers/Architects

Industries

Computer Systems Design ServicesComputing Infrastructure Providers, Data Processing, Web Hosting, and Related ServicesCustom Computer Programming Services
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About the role

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 & DesignDefine 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, DynamoDBDevelop 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 AWSDefine 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:o S3 (data lake design)o AWS Glue (ETL, catalog)o Amazon Redshift (data warehouse design & optimization)o Lambda, Step Functions (orchestration)o IAM, Lake Formation (security)
  • Data Engineering & Processing
  • Strong hands-on experience with:o PySpark / Spark (EMR or Glue)o SQL (advanced level)o Python for data pipelines
  • Experience with streaming (Kinesis / Kafka) is a plus
  • Data Architecture
  • Expertise in:o Data lake / lakehouse architectureso Data modeling (dimensional + normalized)o Metadata and cataloging strategieso Handling large-scale, distributed data systems
  • Modern Data Stack (Preferred)
Exposure to:o dbt, Airflow, Snowflake (optional but valuable)o BI tools (QuickSight, Tableau, Power BI)o API-based ingestion and microservices-based data flowso Amazon Quick Suite (QuickSight, Quick Chat, Quick Flows, Quick Automate, Quick Research)o SQL & Data Modelingo AWS Analytics Stacko Dashboard Designo AI Agent Design & Configurationo Workflow Automation & Business Process Optimization SoftSkillsStrong 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-HaveAWS Certifications (Solutions Architect, Data Analytics Specialty) Experience with data governance frameworks / regulatory compliance Background in large enterprise transformations

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JOB OVERVIEW

Experience level

Lead

Location

Clinton, NJ

Occupation

Database Architects

Industry

Computer Systems Design Services

Posted

today

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