Cloud Data Engineer

Job Description

ECS is seeking a Cloud Data Engineer to work in a hybrid onsite/remote capacity from our Fairfax, VA office as a member of a team implementing a new cloud-based application. This position is contingent upon additional funding. The Cloud Data Engineer will lead, together with an Application Developer, the design and implementation of a new cloud‑based application that will serve as the foundation for future artificial‑intelligence (AI) capabilities.

The incumbent will:

• Gather and analyze customer requirements, data sources, and workflow needs.
• Leverage deep knowledge of cloud platforms (AWS, Azure) and AI technologies to create a production‑ready solution within a Dev Sec Ops  framework.
• Bridge strategy, architecture, and development to help the Department of War (DoW) become more data‑centric and insight‑driven.
• Integrate Commercial‑Off‑The‑Shelf (COTS) products, consume APIs, interact with data repositories, and manage cross‑domain system interfaces.

• Develop a roadmap that links architectural capabilities to the organization’s data challenges.
• Work directly with developers to deliver solutions, provide customer support, and perform solutioning.
• Communicate technical concepts to stakeholders at all levels, building relationships, offering guidance, and articulating business value.
• Mentor data‑engineers, establish best‑practice standards, conduct code reviews, and explain the business impact of solutions.
• Operate in an Agile environment, applying advanced design and engineering best practices.
• Build data‑driven solutions that improve business insight, support operational decisions, and enable performance management.

• U.S. Citizen.
• Ability to obtain and maintain a Top Secret with SCI security clearance.
• Bachelor’s degree in Computer Science, Engineering, Data Science, or related field.
• Active DoD 8140 IAT Level II or higher (e.g., CompTIA Security+) and SAA‑C03 AWS Certified Solutions Architect - Associate certifications.
• 10+ years of experience building analytical tools, including AI/ML‑based solutions.
• Proven record of delivering high‑quality software that is accurate, efficient, reliable, maintainable, and scalable.
• Strong foundation in data‑engineering fundamentals—ingestion, cleaning, transformation, storage, fusion, and visualization.
• Hands‑on experience with cloud‑native data and AI services on AWS and Azure (e.g., S3, Redshift, Athena, Glue, Azure Data Lake, Synapse, Azure Machine Learning, etc.).
• Programming languages:
  Python (primary), Java, Scala or another language; strong SQL skills.
• Data‑orchestration tools:
  Apache Airflow, Azure Data Factory, AWS Step Functions, etc.
• Data‑lake/warehouse platforms:
  Snowflake, Redshift, Synapse, Big Query, Delta Lake.
• Advanced SQL + Python/Scala for ETL, analytics, and model‑serving pipelines.
• Understanding of scaling & performance for distributed/cloud systems.
• Familiarity with AI/ML concepts, automation, and scripting.
• Experience designing Zero‑Trust data architectures—encryption, IAM policies, audit logging.
• Professional software‑development practices: version control (Git), automated testing, code review, and modular design.
• Strong technical writing, presentation, and communication skills for reports, proposals, and stakeholder briefings.
• Translate strategic goals into concrete technical roadmaps.
• Partner with developers to prototype, test, and deploy solutions.
• Serve as a liaison between technical teams and business leadership, ensuring alignment on priorities and outcomes.
• Foster a culture of continuous improvement and knowledge sharing.
• Strong problem‑solving and decision‑making capabilities, with a proven ability to weigh the relative costs and benefits of potential actions and identify the most appropriate solution.
• Highly developed interpersonal and oral/written communication skills, with the ability to effectively and professionally interact with a diverse set of stakeholders (from peers to end‑users to executive management).

• Active Secret clearance.
• Prior experience in data engineering, data science, data architecture, or database/search technologies.
• Experience processing bulk datasets (e.g., terabyte‑scale…