AWS Data Architect
TrianzAbout the role
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
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