AWS Data Architect

Description

Role: AWS Data Architect

Location: [Location(s) / Remote]– Hybrid – Clinton, NJ – 3 days in a week from office

Employment Type: [Full-time /Contract] – Contract

Duration: 3 months

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 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

Why choose Trianz?

• Personal Growth: Startup agility with enterprise impact. Experience rapid innovation cycles while working on Fortune 500 transformations.
• AI-First Future: Where humans and AI revolutionize business. Lead the charge in implementing AI-driven transformation at scale.
• Global Impact: Shape transformation across continents. Work with diverse teams and clients spanning Americas, Europe, Asia, and beyond.
• Executive Access: Direct impact on Fortune 500 strategies. Work alongside C-suite leaders and influence major business decisions.
• Ownership & Entrepreneurial Spirit: Your ideas, our platform, global impact. Zero bureaucracy culture with decision-making autonomy and rapid execution.

Equal Employment Opportunity

Trianz is an Equal Opportunity Employer and does not discriminate based on race, color, creed, national or ethnic origin, gender, religion, disability, age, political affiliation or belief, special needs veteran, veteran of the Vietnam Era, or citizenship status (except in those special circumstances permitted or mandated by law). We comply with all state and federal laws and regulations protecting employees and applicants against illegal discrimination, retaliation, and harassment. Our policy is available upon request. We consider qualified applicants with criminal histories, consistent with applicable federal, state, and local law. Trianz participates in the E-Verify program in certain locations, as required by law. We are committed to providing reasonable accommodation for all qualified individuals with a disability or other reasons protected by applicable laws. If you require assistance or accommodation due to a disability orspecial needs to search for a job opening or apply, please email [email protected] with your request and contact information.

Trianz Privacy Notice

Trianz respects your privacy and wants to ensure we comply with applicable Data Privacy Regulations as per local regulator laws. Please review our privacy policy at https://www.trianz.com/privacy-policy for more.