AWS Cloud Data Engineer

System One is seeking an AWS Cloud Data Engineer to design, build, and maintain scalable data pipelines in AWS, with a focus on ETL and ELT, data modeling, governance, and data quality. This remote, long-term contract role is based in McLean, Virginia and requires the ability to obtain a Federal Public Trust clearance.

Responsibilities

• Design, develop, and sustain scalable data pipelines and processing solutions inside AWS environments.
• Collaborate with AWS cloud DBAs and cross-functional teams to migrate data from legacy systems to AWS while preserving performance, reliability, and security.
• Build ETL and ELT workflows to ingest, transform, and load data into data lakes, data warehouses, and analytic platforms.
• Leverage AWS data services such as S3, Glue, Step Functions, Lambda, Kinesis, EMR, Athena, Redshift, RDS, and Aurora in data engineering workflows.
• Create and maintain data models, schemas, technical documentation, and data access patterns for both transactional and analytical workloads.
• Establish data quality checks, monitoring, alerts, governance controls, and compliance practices for data retention, privacy, and security requirements.

Requirements

• Ability to obtain a Federal Public Trust clearance.
• Bachelor’s degree in Computer Science, Data Engineering, or a related field; four additional years of relevant experience may substitute for a degree.
• Minimum of 6 years of data engineering experience, including at least 3 years in AWS cloud environments.
• Strong experience with AWS data services including S3, Glue, DMS, Athena, Redshift, EMR, Kinesis, and Lambda.
• Proficiency in Python, Scala, or Java for data processing and pipeline development.
• Experience with SQL and relational databases such as PostgreSQL or Oracle, plus NoSQL databases like DynamoDB or DocumentDB.
• An understanding of data modeling concepts for transactional and analytical workloads.
• Experience with Infrastructure as Code tools (Terraform, CloudFormation, or CDK) and CI/CD pipelines for data engineering workflows.
• Strong analytical, problem-solving, collaboration, and communication skills with a focus on data quality and system reliability.

Technologies

• AWS services: S3, Glue, Step Functions, Lambda, Kinesis, EMR, Athena, Redshift, RDS, Aurora
• Programming: Python, Scala, Java
• Databases: PostgreSQL, Oracle, DynamoDB, DocumentDB
• Infrastructure as Code and CI/CD: Terraform, CloudFormation, CDK
• Big data tooling: Apache Spark, Apache Airflow, AWS-native orchestration tools
• Version control and containers: Git, Docker, Kubernetes, ECS, EKS
• BI and visualization: QuickSight, Tableau, Power BI
• Data formats and processing: JSON, Avro, Parquet, ORC

Benefits

• Medical, dental, and vision insurance
• Spending accounts
• Life insurance and voluntary plans
• 401(k) retirement plan

NICE TO HAVE

• AWS Certified Data Engineer – Associate or other relevant AWS certifications (e.g., AWS Solutions Architect)
• Experience with Apache Spark, Apache Airflow, or AWS-native orchestration tools
• Knowledge of data formats such as JSON, Avro, Parquet, ORC and related compression techniques
• Familiarity with Git and collaborative development practices
• Experience with container technologies such as Docker, Kubernetes, ECS, or EKS
• Experience with data visualization tools like QuickSight, Tableau, or Power BI
• Understanding of data privacy regulations and compliance frameworks
• Experience tuning and optimizing distributed data processing systems
• Knowledge of networking, security, and IAM policies related to data engineering workflows