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Department Summary:
The Data Environments and Engineering Department (L146) in the Modeling & Analysis Innovation Center is seeking highly motivated, adaptive, and enthusiastic candidates with a wide variety of interests and a foundation of skills in systems engineering, software engineering, information systems, or data engineering to join our department as a Senior Data Engineer. Candidates should have a strong interest in addressing and solving challenges related to capturing, managing, and sharing data supporting decision making and enabling mission processes.
Roles and Responsibilities:
- Designing and building prototypes for ingesting, curating, and analyzing data at scale.
- Collecting and preparing data for use by data scientists and analysts.
- Supporting stakeholder interviews to determine data requirements and define data flows.
- Documenting data transformation rules to meet the requirements for system interfaces and data integration projects.
- Performing data profiling to identify quality gaps and determine if data is fit for use for its intended purpose.
- Researching and evaluating data engineering tools and technologies.
- Leading or supporting sponsor work conducted in a lab environment.
Basic Qualifications:
- Typically requires a minimum of 5 years of related experience with a bachelor’s degree; or 3 years and a master’s degree; or a PhD without experience; or equivalent combination of related education and work experience.
- Secret clearance is required.
- Strong developer skills using SQL and Python.
- Hands-on experience with one or more database technologies (e.g., PostgreSQL, Oracle, MySQL, SQL Server, DB2, MongoDB, Neo4j, Couchbase, Cassandra).
- Excellent written and verbal communications skills with ability to describe and present complex technical concepts in relatable terms.
- Strong knowledge of ETL/ELT processes, tools, and frameworks.
- Experience with large scale data architectures, including analysis of alternatives, technical product evaluations, requirements analysis, design, data systems prototyping, and process automation.
- Experience building conceptual, logical, and physical data models.
- Knowledge of cloud platforms and technologies such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform.
- Proficiency in one or more modern programming languages such as Python, R, Scala, C++, Java, C#, and JavaScript.
- Data Engineering skills to include expertise in preparing data for analysis, strong understanding of data science concepts, experience with BI tools, and understanding ML frameworks, algorithms, and libraries.
- Applied mathematics: probability and statistics.
- Strong innovation, problem-solving, systems analysis, planning, organizational, and interpersonal skills.
- Knowledge of data management practices that align with modern/emerging analytics techniques.
- Desire to continuously learn new techniques and evolve approaches by regularly engaging in structured educational pursuits, personal research, and outreach to subject matter experts across the corporation.
Preferred Qualifications:
- Master’s degree in computer science, data science, systems engineering, software engineering, or information systems.
- Experience migrating legacy data systems to new/modernized platforms.
- Hands-on experience with data flow and pipeline frameworks such as Kafka, NiFi, Spark, Airflow, and Hadoop.
- Familiarity with microservice architectures, data warehousing, data fabric, data lakes, and data mesh.
- Understanding the use of data in AI/ML and LLM.
- Knowledge and experience across data management domains, including data science, data governance, metadata management, data quality, business intelligence, data security & privacy, and data strategy.
- Experience performing source to target data mapping.
- Knowledge of natural language processing techniques.
This requisition requires the candidate to have a minimum of the following clearance(s): Secret
This requisition requires the hired candidate to have or obtain, within one year from the date of hire, the following clearance(s): Secret
Work Location Type: Hybrid
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