AWS Cloud Data Engineer

System One presents a remote, long-term contract opportunity for an AWS Cloud Data Engineer based in McLean, VA. In this role you will design, build, and maintain scalable data pipelines in AWS, with a focus on ETL/ELT, data modeling, governance, and data quality. A Federal Public Trust clearance is required.

Benefits

• Medical insurance
• Dental insurance
• Vision insurance
• Spending accounts
• Life insurance
• Voluntary plans
• 401(k) plan

Responsibilities

• Design, build, and maintain scalable data pipelines and processing solutions within AWS cloud environments.
• Collaborate with AWS Cloud DBAs and cross-functional teams to migrate data from legacy applications to AWS while ensuring performance, reliability, and security.
• Develop ETL/ELT workflows to ingest, transform, and load data into data lakes, data warehouses, and analytical platforms.
• Implement AWS data services, including S3, Glue, Step Functions, Lambda, Kinesis, EMR, Athena, Redshift, RDS, and Aurora.
• Create and maintain data models, schemas, technical documentation, and data access patterns for transactional and analytical workloads.
• Establish data quality checks, monitoring, alerting, 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, relational databases such as PostgreSQL or Oracle, and NoSQL databases such as DynamoDB or DocumentDB.
• Understanding of data modeling concepts for transactional and analytical workloads.
• Experience with Infrastructure as Code tools such as 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.

Nice to Have

• AWS Certified Data Engineer – Associate certification.
• AWS Certified Solutions Architect or other relevant AWS certifications.
• Experience with Apache Spark, Apache Airflow, or AWS-native orchestration tools.
• Knowledge of data formats such as JSON, Avro, Parquet, and ORC, including compression techniques for efficient storage and processing.
• Familiarity with Git and collaborative development practices.
• Knowledge of container technologies, including Docker, Kubernetes, ECS, or EKS.
• Experience with data visualization tools such as 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.

Technologies

• S3, Glue, Step Functions, Lambda, Kinesis, EMR, Athena, Redshift, RDS, Aurora
• Python, Scala, Java
• SQL, PostgreSQL, Oracle
• DynamoDB, DocumentDB
• Terraform, CloudFormation, CDK
• Apache Spark, Apache Airflow
• Git, Docker, Kubernetes, ECS, EKS
• QuickSight, Tableau, Power BI
• JSON, Avro, Parquet, ORC