ETL Java/NiFi Engineer – Cloud Data Lake & DevOps

Leidos LLC; Plyers Mill Estates (MD); On-site; USD 70,000 - 126,000; Full time

Benefits offered by this job

Paid Time Off

11 holidays

401K with company match

Flexible schedules

Stock purchase plan

Upskilling

Education and training support

Parental paid leave

Job summary

Leidos has an exciting opportunity for an ETL Java Developer in the Intel Security Sector. The role focuses on building NiFi-based ETL data pipelines, optimizing data flows, and supporting enterprise-scale data ingestion into a Data Lake within a DevOps framework.

You will design, implement, and test customer tools and applications for data extraction, transformation, and loading, with emphasis on secure, scalable, and observable data pipelines across diverse sources and stores.

Qualifications

• Experience with NiFi data pipelines in enterprise environments.
• Proficiency in Java and/or Python with automation scripting.
• Experience with cloud platforms such as AWS, Azure, or OCI.
• Ability to analyze data challenges and propose solutions.
• Active TS/SCI clearance with polygraph required.
• Bachelor's degree with 2–4 years of relevant experience.

Responsibilities

• Build enterprise-level NiFi data pipelines for large-scale data ingestion and transformation.
• Tune and optimize NiFi data flows for batch and real-time processing.
• Troubleshoot data flow issues, performance bottlenecks, and integration failures.
• Follow best practices for NiFi development, security, and governance.
• Create and maintain documentation for NiFi data flows and architectures.
• Collaborate with data architects, engineers, and developers to translate requirements into robust solutions.

Skills

Java

Python

Scripting

AWS/Azure/OCI

Data engineering

Teamwork

DevOps

Education

Bachelor's degree

Tools

NiFi

NiFi Registry

Clustering

Job description

Leidos has an exciting opportunity for an ETL Java Developer in the Intel Security Sector. The role focuses on building NiFi-based ETL data pipelines, optimizing data flows, and supporting enterprise-scale data ingestion into a Data Lake within a DevOps framework.

You will design, implement, and test customer tools and applications for data extraction, transformation, and loading, with emphasis on secure, scalable, and observable data pipelines across diverse sources and stores.