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

Education:

Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent experience