AWS Data Engineer

Position Summary

Fourways Consulting is actively seeking 10 experienced, senior-level AWS Data Engineers to drive enterprise-scale big data engineering initiatives in Atlanta, Georgia. In this high-impact technical role, you will take ownership of architecting, deploying, and optimizing robust, high-throughput cloud data pipelines, distributed analytics engines, and mission-critical data lake environments across Amazon Web Services. With over a decade of dedicated professional engineering experience, you will bridge scalable distributed processing with modern data warehousing and infrastructure-as-code automation.

This position represents an outstanding full-time career opportunity for accomplished data engineering leaders to transform raw enterprise datasets into actionable analytical assets within a dynamic technology consulting landscape.

As an AWS Data Engineer with Fourways Consulting in Atlanta, GA, you will serve as a technical subject matter expert responsible for the end-to-end design, implementation, and performance optimization of modern big data architectures. Collaborating closely with cross-functional teams of software architects, data scientists, machine learning engineers, and executive business stakeholders, you will build and govern scalable data pipelines that process petabyte-scale structured and unstructured datasets with low latency and high availability.

Your core technical mandate spans engineering distributed data processing workflows utilizing Apache Spark, Hadoop, and Hive, and orchestrating native AWS serverless and managed services including AWS EMR, AWS Glue, AWS Lambda, Amazon S3, and Amazon Redshift. You will design, develop, and secure high-performance RESTful APIs for real-time and batch data delivery, write optimized SQL queries, and automate cloud infrastructure provisioning using Terraform.

Additionally, you will establish disciplined CI/CD deployment pipelines utilizing Git Lab, enforce automated data quality monitoring, and implement stringent data security, encryption, and governance protocols. This role requires exceptional analytical problem-solving skills, deep cloud architecture acumen, and full readiness to complete a mandatory in-person interview in Atlanta, GA.

• Architect, develop, and optimize robust, scalable end-to-end big data pipelines and ETL/ELT workflows across AWS cloud environments.
• Build and maintain distributed, high-volume data processing jobs utilizing Apache Spark, PySpark, Hadoop, and Hive on AWS EMR.
• Design and implement serverless data ingestion and transformation pipelines utilizing AWS Glue, AWS Lambda, Amazon S3, and Amazon Event Bridge.
• Model, optimize, and manage enterprise cloud data warehouses and analytical databases utilizing Amazon Redshift and advanced SQL tuning.
• Develop, secure, and deploy high-performance RESTful APIs to facilitate seamless data integration between enterprise applications and analytical platforms.
• Automate, manage, and maintain cloud infrastructure-as-code (IaC) provisioning across AWS environments using Terraform.
• Establish, streamline, and govern automated continuous integration and continuous delivery (CI/CD) pipelines utilizing Git Lab CI/CD.
• Enforce comprehensive data governance, pipeline observability, data quality validation frameworks, and enterprise encryption standards.

• Minimum 10+ years of dedicated professional experience in Big Data Engineering, Data Platform Architecture, or Software Engineering.
• Advanced programming and scripting proficiency in Python for complex data transformations, automation, and distributed systems integration.
• Extensive hands-on technical architecture and engineering experience with core AWS big data services: EMR, Lambda, Glue, S3, and Redshift.
• Deep technical expertise in Apache Spark, PySpark, Hadoop ecosystem, and Apache Hive for distributed batch and streaming data processing.
• Expertise in relational and analytical database modeling, advanced SQL development, index tuning, and performance profiling.
• Proven experience designing, building, testing, and deploying secure enterprise-grade RESTful APIs for data delivery.
• Hands-on expertise implementing Infrastructure as Code (IaC) utilizing Terraform for automated AWS cloud deployments.
• Demonstrated mastery of Git Lab CI/CD pipelines, Git version control, automated testing, and agile software development workflows.

• Recognized AWS cloud certifications such as…