Cloud Data Engineer

Job Description

Job Description

Peerless is searching for an experienced Cloud Data Engineer to be responsible for designing, building, and maintaining scalable, secure, and efficient data infrastructure and pipelines in cloud environments. Your work ensures that large volumes of data are stored, processed, and made available for analysis while meeting business needs and compliance requirements.

Required Skills

• Must be a US citizen with the ability to get a Top Secret Clearance
• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related STEM field (Master’s preferred).
• 5+ years of relevant work experience in data engineering, database administration, or object storage management.
• Must possess an IAT Level II certification (e.g., Security+, CCNA Security, CySA+)

Required Qualifications:

• Proven experience managing databases and object storage solutions across on-premises, cloud, inter-region, and inter-cloud platforms.
• Expertise in cloud platforms such as AWS, Google Cloud, or Microsoft Azure.
• Hands-on experience with object storage technologies (e.g., AWS S3, MinIO, Ceph) and data transformation pipelines (e.g., Apache Airflow, Argo Workflows, Python).
• Strong proficiency in Python, SQL, and modern data engineering frameworks.
• Familiarity with both relational (e.g., Oracle, PostgreSQL) and non-relational databases (e.g., MongoDB, Cassandra).
• Experience with data tiering, record/object-level authorization, and secure data handling.
• Ability to handle multiple projects and deadlines in a fast-paced environment.

Desired Qualifications:

• Experience supporting Intelligence Community (IC) mission programs.
• Knowledge of data catalogs, search/indexing, and discovery tools.
• Experience with streaming data (e.g., Kafka) and event-driven architectures.
• Familiarity with DevSecOps, security scanning, and accreditation processes.
• Understanding of analytics, machine learning (ML), or exploitation workflows consuming large datasets.
• Prior experience modernizing or migrating legacy data systems.