Senior Data Engineer

Come put your data and software engineering skills into action! The Leidos Office of Technology has openings for talented Data Engineers to join our team and develop reusable solutions that support our customers in any environment. you’ll leverage your expertise to develop scalable, high-performance data pipelines and solutions.

You will work closely with multiple teams to identify challenges, design data architectures, and provide actionable insights to drive business outcomes. In this role, you’ll contribute to the full software development lifecycle, ensuring the efficient processing, storage, and retrieval of data in complex cloud environments. As a well-rounded software engineer, you’ll also play a key role in helping teams design software solutions that seamlessly integrate with data systems. You will be intellectually challenged and provided with a tremendous opportunity for growth in a fast-paced, and fun environment.

Primary Responsibilities
•Design, implement, and maintain robust, scalable data pipelines that support real-time and batch processing.
•Collaborate with software and DevOps teams to develop data architectures that optimize performance, security, and scalability.
•Automate data workflows and ETL processes, ensuring seamless integration between cloud-based and on-premise systems.
•Build and maintain databases, data warehouses, and data lakes that meet the needs of a variety of customers and use cases.
•Monitor data pipelines and ensure the integrity, quality, and availability of data across systems.
•Optimize data storage, retrieval, and reporting performance across cloud and hybrid environments.
•Break down high-level requirements into actionable tasks and collaborate with cross-functional teams to solve technical challenges.
•Mentor junior engineers, review code, and promote best practices for software engineering and data architecture.

Basic Qualifications
•Bachelor’s degree in Computer Science, Data Engineering, or a related discipline, with 4–8 years of experience in data engineering or software development, or a Master’s degree with 2–6 years of experience. Additional experience may be considered in lieu of degree.
•Strong proficiency in Python, Java, or similar programming languages.
•Experience designing, building, and managing data pipelines and architectures using cloud services (e.g., AWS, Azure, Google Cloud Platform).
•Solid understanding of databases (SQL/NoSQL), ETL processes, and data warehousing solutions.
•Proficiency in containerization technologies such as Docker and orchestration tools like Kubernetes.
•Experience with automation tools like Terraform, Ansible, or similar for data infrastructure management.
•Strong problem-solving and communication skills with the ability to work independently or as part of a team.
•Ability to obtain a U.S. DoD Secret security clearance.

Preferred Qualifications
•Expertise in distributed data storage technologies such as Hadoop, Spark, or similar frameworks.
•Experience with data governance, data security, and compliance frameworks in highly regulated environments.
•Familiarity with CI/CD pipelines and automated deployment strategies for data solutions.
•Knowledge of machine learning workflows and experience deploying models in production environments.
•Familiarity with GitOps tools (e.g., Argo CD, Flux CD) for managing infrastructure as code.
•Professional certifications related to data engineering or cloud technologies (e.g., AWS Certified Data Analytics, Google Cloud Data Engineer).

Original Posting Date:

While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.