Senior Data Engineer
3 weeks ago
This role involves developing and implementing statistical and modern analytical methods to improve operations and maintenance of the Arnold Engineering Development Complex (AEDC) air and space ground test equipment and facilities.
The successful candidate will work as a member of the Digital Enterprise group (DE) in the Mission Support Branch to lead implementation of data-centered projects to improve the AEDC ground test data infrastructure, facility operations, and business systems.
The person selected for this role will work closely with multidisciplinary work teams throughout the organization to identify opportunities for leveraging data to drive decisions and will help design and implement a data architecture working with the Digital Enterprise team.
Key Responsibilities:
Develop and implement data-engineering strategies and programs.
Utilize test data sources to optimize data analytics at AEDC and suggest ways which insights obtained might be used to inform testing sustainment and operational strategies.
Automate manual processes, optimizing data delivery, re-designing infrastructure for greater scalability.
Utilize machine learning tools to select features, create, and optimize classifiers.
Define & develop approaches and demonstrate abilities to mine and analyze data from databases to drive optimization and improvement of data collected at AEDC.
Identify and assess the effectiveness of data engineering, data sources and data gathering techniques.
Utilize applicable experience in big data , analytics, algorithmic, custom data models, algorithms and/or machine learning approaches to help extract data that will help drive engineering decisions.
Coordinate with different multidisciplinary teams to implement models and monitor outcomes.
Define & develop processes and tools to monitor and analyze model performance and data accuracy.
Define & develop the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and big data' technologies.
Requirements:
B.S. in Computer Science, Statistics, Mathematics, Engineering or another relevant engineering field from an accredited university program plus a minimum of 6 to 14 years of progressive and relevant experience.
Current U.S. Citizenship is required.
Preferred Qualifications: Master's or PhD degree in Computer Science, Statistics, Mathematics, Physics, Engineering or another relevant engineering field from an accredited university program.
Experience with development lifecycle methodologies such as Agile DevSecOps.
Experience with data scripting language software like Python, Java, C++, or Ruby and SQL.
Experience with data extraction tools and processes, data ingestion, ETL, data mining, API's and data warehousing.
Demonstrated experience in a data engineering role.
Experience working with and creating data architectures.
Knowledge of a variety of machine learning techniques and their real-world advantages/drawbacks.
Coding knowledge and experience with multiple languages
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