AWS Data Architect

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:

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 architectures

o Data modeling (dimensional normalized)

o Metadata and cataloging strategies

o 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 flows

o Amazon Quick Suite (QuickSight, Quick Chat, Quick Flows, Quick Automate, Quick Research)

o SQL & Data Modeling

o AWS Analytics Stack

o Dashboard Design

o AI Agent Design & Configuration

o 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