AWS Data Architect

TalentOla; Atlanta (GA); On-site; USD 110,000 - 117,000; Full time

Job summary

Talentola is seeking a visionary Senior Data Architect to lead the design, development, and optimization of our enterprise data ecosystem on AWS. You will architect data pipelines, modern data lakes/warehouses, and real-time streaming architectures powering core enterprise applications and analytics platforms.

With 10+ years in IT and 5+ years in data architecture, you will partner with stakeholders, translate complex rules into executable designs, and guide the team through hands-on

Qualifications

• 10+ years in IT with 5+ years in data architecture and data warehousing.
• Experience designing cloud data architectures on AWS.
• Expertise in ETL automation and data pipelines.
• Knowledge of GDPR, CCPA, SOC2 governance.
• Proficient in SQL and Python.
• Familiar with IaC tools like Terraform or CloudFormation.

Responsibilities

• Translate requirements into robust data designs.
• Design scalable cloud data structures on AWS.
• Modernize on-premises systems to cloud-native data stores.
• Define data collection, transformation, storage, and freshness.
• Lead governance, security, and collaboration across teams.

Skills

SQL

Python

Tools

Apache Airflow

Terraform

CloudFormation

AWS Glue

Kinesis

Redshift

Job description

Data Architect

• 80-85 Max rate Atlanta GA (Onsite)
• Mphasis /Delta Airlines

Exp: 10+ years in IT, with at least 5+ years specializing in data architecture, data warehousing, and large-scale data engineering.

We are seeking a visionary and hands-on Senior Data Architect to spearhead the design, development, and optimization of our enterprise data ecosystem on AWS. In this role, you will bridge the gap between complex business requirements and robust, scalable cloud infrastructure. You will architect enterprise-grade data pipelines, modern data lakes/warehouses, and real-time streaming architectures that power our core enterprise applications and analytics platforms.

Key Responsibilities

Requirements Translation & Business Partnership

Partner closely with business stakeholders and technical SMEs to identify required data, locate source systems, and translate complex business rules into clear, actionable data requirements and robust solution designs.

Cloud Data Architecture & Scalability

Design and evaluate scalable cloud data structures and warehousing solutions on AWS that expertly support application needs, current data volumes, and long-term future growth.

Modernize legacy on-premises data systems and monolithic databases into cloud-native, microservices-friendly data stores.

Data Integration & Process Design

Define how data is collected, transformed, stored, and kept current across the enterprise.

Leverage deep experience in ETL automation and orchestration to build reliable, maintainable, and high-performance data pipelines.

Technical Execution & Guidance (SQL & Python)

Bring practical, hands-on experience manipulating data and implementing complex transformation logic.

Provide the technical depth needed to validate results, troubleshoot complex data issues, and guide developers through hands-on implementation.

Governance, Security & Collaboration

Establish enterprise-wide data governance, metadata management, and compliance controls (GDPR, CCPA, SOC2) using tools like AWS Lake Formation and the Glue Data Catalog.

Collaborate with Enterprise Architects, Software Engineers, and DevOps to align data patterns with application requirements and CI/CD pipelines.

Required Qualifications & Skills

Experience: 10+ years in IT, with at least 5+ years specializing in data architecture, data warehousing, and large-scale data engineering.

AWS Expertise: Deep, hands-on experience designing architectures using core AWS data services:

Storage & Warehousing: Amazon Redshift, Amazon S3, Amazon DynamoDB, Amazon Aurora / RDS.

Processing & Ingestion: AWS Glue, Amazon Kinesis, Amazon EMR, AWS Lambda, MSK (Managed Streaming for Apache Kafka).

Governance & Security: AWS Lake Formation, IAM, KMS.

Technical Stack:

Advanced proficiency in SQL and programming languages like Python (or Scala) for data manipulation and transformation logic.

Experience with orchestration tools (e.g., Apache Airflow, AWS Step Functions) and Infrastructure as Code (Terraform, AWS CloudFormation).

Certifications:

AWS Certified Data Analytics - Specialty or AWS Certified Solutions Architect (Professional preferred).