Junior Data Engineer

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

LMI is seeking a Junior Data Engineer to support a Special Operations customer in Tampa, FL.

This position is on-site at MacDill Air Force Base in Tampa, FL with flexibility for telework.

Responsibilities may include:

• 1+ years applying data engineering, data cleansing, data mining, statistics, machine learning or analytic approaches to answer key intelligence questions, producing results and re-usable products that provide value to Intelligence Analysts.
• Design and develop data pipelines that support advanced analytics workflows.
• Help grow a trusted data foundation through ETL, data streaming, and data processing across distributed systems.
• Training within Databricks and Qlik with the opportunity to work in Advana.
• Develop and maintain documentation that enable platform maintenance and front-office knowledge management.
• Participate in infrastructure reviews to identify best practices and opportunities for improvement.
• Work with analysts to interpret analytic results and refine analysis as needed. Collaborate with Intelligence Analysts to understand needs and devise possible solutions.
• Communicate results and ideas to key decision makers, analysts and other stakeholders. Contractor shall advise on the interpretation and use of data intelligence products, quality assessments and applications.

QUALIFICATIONS:

• Bachelors degree in Computer Science, Data Engineering, Data Science, Statistics, Applied Math, or related STEM field is required. Master’s degree is preferred
• 1+ years of related experience required
• Ability to obtain an interim Secret clearance in a timely manner is required. TS/SCI clearance is preferred. 
• Must be proficient with at least one programming language (Java, C++, Python, R, etc.)
• Proficient in Agile Development and Git Operations
• Demonstrated experience applying data science methods to real-world data problems
• Outstanding communication skills, written and verbal
• Highly organized and able to manage multiple projects simultaneously
• Team-player mentality with a positive attitude
• Keen attention to detail and solid analytical skills
• Able to articulate complex, abstract concepts concisely and effectively

Languages, Tools, and Techniques

• Demonstrated proficiency with Python and SQL to manipulate data and draw insights from large data sets.
• Demonstrated proficiency in a variety of supervised and unsupervised machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Demonstrated proficiency in advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
• Demonstrated proficiency with common data science libraries.
• Demonstrated proficiency visualizing/presenting data for stakeholders.
• Capability to recognize when Data Engineering can add value to an intelligence problem, and when it cannot.