Data Engineer (Backend & AWS)

Job Title: Data Engineer (Backend & AWS)
Location: Charlotte NC (Hybrid)
Duration: 12 Months

Role Overview

We are looking for a highly skilled Data Engineer with strong backend development expertise and deep knowledge of AWS cloud technologies. This role focuses on designing building and optimizing scalable data pipelines and backend systems that power data-driven applications analytics and business intelligence initiatives.

Key Responsibilities

• Design develop and maintain scalable data pipelines and ETL/ELT processes using modern cloud and big data technologies.
• Build and enhance backend services and APIs to support data-driven applications and integrations.
• Leverage AWS services to architect and deploy reliable secure and high-performance data solutions.
• Collaborate with data scientists analysts and business stakeholders to translate data requirements into technical solutions.
• Optimize data workflows for performance scalability and cost efficiency.
• Implement and enforce data quality governance and security best practices.
• Work with cross-functional teams in an Agile/Scrum environment to deliver high-quality solutions.
• Monitor troubleshoot and resolve issues in data pipelines and backend systems.
• Contribute to architecture decisions including data modeling and system design.

Required Qualifications

• Bachelors degree in Computer Science Engineering or a related field.
• 5 years of experience in Data Engineering and/or Backend Development.
• Strong programming skills in Python Java or Scala.
• Hands-on experience with AWS services such as S3 Lambda Glue Redshift EMR or Athena.
• Proven experience building data pipelines ETL/ELT processes and data integration workflows.
• Solid experience with backend frameworks such as Spring Boot or .
• Strong knowledge of SQL databases (PostgreSQL MySQL) and NoSQL databases (DynamoDB MongoDB).
• Understanding of data modeling data warehousing and distributed systems.

Preferred Qualifications

• Experience with big data technologies such as Apache Spark and Hadoop.
• Familiarity with containerization and orchestration tools like Docker and Kubernetes.
• Experience with Infrastructure as Code (IaC) tools such as Terraform or AWS CloudFormation.
• Exposure to real-time/streaming data pipelines (Kafka Kinesis etc.).
• Knowledge of CI/CD pipelines and DevOps practices.

Nice to Have

• Experience in energy/utilities domain or working with large enterprise clients.
• Exposure to data governance and compliance frameworks.