AWS Data Architect

Data Architecture & Strategy

AWS Data Platform Design

Data Lakehouse & Data Warehouse

Data Governance & Security

Data Integration & Engineering

Required Qualifications

• Bachelor's or master's degree in engineering, or related field.
• 10+ years of experience in Data Architecture, Data Engineering, or Data Platform Management.
• 5+ years of experience in AWS cloud-based data solutions.
• Strong expertise in:
• Data Lakehouse Architecture
• Enterprise Data Warehouse Design
• Data Modeling (Dimensional & Data Vault)
• ETL/ELT Frameworks
• Big Data Technologies
• Hands-on experience with SQL and Python.
• Strong understanding of cloud-native architecture principles.
• Required Technical Skills
• AWS
• Amazon S3
• AWS Glue
• AWS Lake Formation
• Amazon Redshift
• Amazon Athena
• Amazon EMR
• AWS Lambda
• Amazon Kinesis
• AWS IAM
• AWS CloudFormation/Terraform
• Databases & Warehousing
• Snowflake
• PostgreSQL
• SQL Server
• Oracle
• MySQL
• Big Data & Lakehouse
• Databricks
• Delta Lake
• Apache Spark
• Apache Iceberg
• Apache Hudi

AWS

Databases & Warehousing

Big Data & Lakehouse

Preferred Certifications

• AWS Certified Solutions Architect – Professional
• AWS Certified Data Engineer – Associate
• AWS Certified Data Analytics – Specialty
• Databricks Certified Data Engineer
• Snowflake Certification
• Ideal Candidate: An AWS Data Architect who can lead data modernization initiatives, drive Data Lakehouse adoption, and deliver scalable, secure, and high-performance analytics platforms supporting business growth and digital transformation.

Responsibilities

• Define and implement enterprise data architecture roadmap aligned with business objectives.
• Design scalable Data Lakehouse and Data Warehouse solutions on AWS.
• Establish data modeling standards, architecture frameworks, and best practices.
• Develop data integration strategies for structured, semi-structured, and unstructured datasets.
• Collaborate with business stakeholders, analytics teams, and IT leadership to deliver data-driven solutions.
• Architect end-to-end data solutions using AWS services
• Design secure and high-performing cloud-native data platforms.
• Optimize data storage, data processing, and query performance.
• Implement modern Lakehouse architectures using technologies such as:
• Databricks
• Delta Lake
• Apache Iceberg
• Apache Hudi
• Design dimensional and enterprise data warehouse models.
• Create scalable ETL/ELT frameworks to support analytics and reporting requirements.
• Enable real-time and batch data processing capabilities.
• Implement data governance, metadata management, lineage, and data quality frameworks.
• Ensure compliance with security and regulatory requirements.
• Define role-based access controls and data protection strategies.
• Partner with cybersecurity teams to maintain data security standards.
• Design and oversee enterprise data pipelines.
• Lead cloud migration initiatives from legacy on-premise platforms to AWS.
• Integrate ERP, CRM, eCommerce, supply chain, finance, and third-party systems.
• Drive automation and CI/CD practices for data platform deployments.