Familiarity with Hadoop-based technologies (Cloudera, Hortonworks)
Experience with NoSQL databases (e.g., MongoDB, Cassandra)
Skilled in data modeling using ERWin or Visio
Degree in a relevant field (Bachelor's or Master's)
Responsibilities
Engineer big data solutions and multi-tiered data environments
Lead initiatives to derive actionable insights from big data
Design data models using enterprise data modeling tools
Build high-performance algorithms and data models in programming languages like Python and Java
Analyze and develop processes for data ingestion, modeling, and mining
Provide AI roadmap and governance for model validation
Create ROI business cases for AI initiatives
Benefits
Comprehensive health insurance
Retirement savings plan
Professional development opportunities
Flexible work arrangements
Supportive team environment
Full Job Description
Project Overview
The DLA Procurement Integrated Enterprise Environment (PIEE) Development and Sustainment program supports modernization, enhancement, and sustainment of a mission-critical defense procurement and payment platform comprising approximately 34 applications.
The program focuses on enterprise software modernization, legacy-code refactoring, Agile/DevSecOps delivery, AWS GovCloud operations, CI/CD automation, cybersecurity, AI/ML integration, automated testing, and improved system performance and user experience.
Responsibilities
Responsible for the engineering of big data solutions and multi-tiered data environments.
Leads initiatives utilizing big data solutions to provide actionable insights for addressing strategic and tactical mission objectives.
Designs data models using Enterprise Data modeling tools (ERwin, Visio).
Builds high-performance algorithms, prototypes, and data models using required programing languages (e.g., Python, C/C++, Java, Perl, Scala). Analyzes and develops data set processes for data ingestion, modeling, and mining.
Provide AI roadmap, ROI business cases, model validation and governance.
Minimum Requirements:
Note: Candidates who do not have the mandatory skills will not be considered
Must have Active Secret Clearance
Minimum 8 years of experience.
Experience engineering large scale big data deployments in Government and large commercial environments.
Experience with ML, NLP, MLOps, Python, data engineering, responsible AI
Experience with Hadoop-based technologies (Cloudera, Hortonworks, MapReduce, Hive, HDFS).
Experience with NoSQL technologies (e.g., MongoDB, Cassandra)
Experience designing data models using Enterprise Data modeling tools (ERWin, Visio).
Experience integrating Big Data solutions with SAP technologies.
