Poly

Peraton•Annapolis Junction, MD

22h•Onsite

About The Position

The Software Engineer supports a suite of web-based applications that automate data management for intelligence community data custodians. These products facilitate information capture and approvals so data can move through the customer mission space compliantly, while standardizing and simplifying data movement, reuse, and integration with downstream tools. The work is performed out of a Peraton facility and offers flexible hours. The role focuses on extracting meaning and value from structured and unstructured data, using statistical methods and machine learning to identify patterns and behaviors, and presenting focused datasets through query and visualization tools. The Software Engineer works with metadata domains to develop automated data characterization methods, supports requirements for characterizing and ingesting data types, and collaborates with customer teams to understand mission needs. The team values expertise in data enrichment and conversion, data ontologies and schemas, structured data formats, and databases. Java, Python, analytic development, and working knowledge of NiFi are highly desired. This position requires an active TS/SCI clearance with a current polygraph. The stated target salary range is $146,000–$234,000. Employees may be eligible for overtime, shift differential, and a discretionary bonus, depending on the position.

Requirements

Fourteen years of experience as a Software Engineer supporting programs and contracts of similar scope, type, and complexity.
At least six recent years of development experience.
Bachelor’s degree in computer science or a related discipline from an accredited college or university; four additional years of SWE experience on projects with similar software processes may substitute for the degree.
Active TS/SCI security clearance with a current polygraph.
Knowledge of data enrichment and conversion methods.
Familiarity with data ontologies and schemas.
Strong knowledge of structured data types, including XML, CSV, and JSON.
Database experience.

Nice To Haves

Java and Python experience.
Analytic development experience.
Working knowledge of NiFi.
Experience using scripting languages such as Python and Scala with statistical libraries to analyze data.
Experience with big data processing frameworks such as Pig, MapReduce, and Spark to scale algorithms over large volumes of data.
Experience combining two or more of analysis, computer science, mathematics, and software engineering to extract meaning and value from large datasets.
Experience with predictive analytics, machine learning, and data mining.
Experience with data flows, Pig scripting, Hadoop MapReduce, and analytic tools.
Experience working with development and systems engineering teams, stakeholders, agencies, and leadership.
Knowledge of data indexing and analytic development.
Experience working with cloud service providers and data stewards.
Demonstrated experience in network metadata processing, manipulation, and analysis in support of intelligence analysis.

Responsibilities

Devise strategies to extract meaning and value from structured and unstructured data.
Use statistical methods and/or machine learning to discover patterns and behaviors of entities.
Use query and visualization tools, such as DataXplorer and GMAE, to present question-focused datasets in a story-like manner.
Work with metadata domains to develop methodologies and techniques for automated data characterization.
Analyze and develop requirements to support the characterization and ingestion of new and existing data types.
Collaborate with customer teams to understand direct mission needs and requirements.
Recommend new technologies and processes for complex software projects.
Serve as the technical lead of multiple software development teams.
Select the software development process in coordination with the customer and system engineering.
Ensure quality control of developed and modified software.
Delegate programming and testing responsibilities to one or more teams and monitor their performance.
Develop simple data queries for existing or proposed databases or data repositories.