AWS Data Architect

Introduction

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.

Responsibilities

• 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)
• E stablish standards for data modeling, partitioning, metadata, and lifecycle management
• Architect solutions for both batch and real-time data processing
• Build and implement pipelines using AWS Glue, EMR, Lambda, Step Functions
• Design data storage using S3, Redshift, RDS, DynamoDB

Requirements

Required Skills:

• 12+ years of experience, including 5 to 7 years in AWS Data Architecture
• Deep experience with S3, AWS Glue, Amazon Redshift, Lambda, Step Functions, IAM, Lake Formation
• Strong hands-on experience with PySpark / Spark, SQL, Python for data pipelines
• Expertise in data lake/lakehouse architectures, data modeling, metadata and cataloging strategies, handling large-scale, distributed data systems

Preferred Skills:

• Experience with dbt, Airflow, Snowflake
• Experience with BI tools such as QuickSight, Tableau, Power BI
• Experience with API-based ingestion and microservices-based data flows
• Experience with SQL & Data Modeling

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