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AWS Data Architect

Turing IT LabsClinton, NJ🇺🇸United StatesPosted 8 Jul 2026

Quick Overview

Work Type
On Site
Level
Mid Senior

Job Description

Job Title: AWS Data Architect

Location: Clinton, NJ – 3 Days Onsite

Duration: 3+ Months Contract

 

Job Description:

Company Overview  

Trianz is an applied AI solutions company that accelerates customer business transformation through AI powered "Transformation Services as a Software Model". With 25+ years of transforming enterprises, we''ve evolved to a product-led, platform-driven organization serving global enterprises across Financial Services, Insurance, Healthcare, Hi-Tech, Manufacturing, and other industries.  

With global presence across 4 continents, our platform portfolio under the unified Concierto brand delivers end-to-end transformations including solutions for Migrate, Manage, Maximize, Modernize, Insights & Agentic AI, and SecOps - delivered through strategic partnerships with leading hyperscalers.  

We''re building the premier innovation-led organization in the digital transformation space through AI-first methodologies and data-driven excellence - RevolutionAIzing Transformations.

 

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 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

Skills

DynamoDB
Microservices
SQL
AWS
ETL
Encryption
Snowflake
Tableau
Airflow
Hadoop
Kafka
Power BI
Python
Redshift
dbt

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