Job description
Overview:
SPA has a requirement for a Data Engineer to support the Data Science & Artificial Intelligence section located at HQ SACT, Norfolk,VA. Responsibilities:
Systems Planning and Analysis, Inc. (SPA) delivers high-impact, technical solutions to complex national security issues. As we enter our 50th year in business, we are known for continuous innovation for government customers, both long-established and newly acquired, as our capabilities expand around the globe. Our work is state-of-the-art and made possible only through the best personnel, tools, and jobs in the national security business. We are highly collaborative in spirit and practice, and we freely share expertise across SPA in our quest for enduring solutions to critical concerns. Come work with the best!
SPA has a requirement for a Data Engineer to support the Data Science & Artificial Intelligence section located at HQ SACT, Norfolk,VA.
- Contribute to the development and implementation of an enabling data science and AI capability at HQ SACT and for the NATO;
- Contribute to ML/AI initiatives across HQ SACT and the NATO Enterprise with a particular focus on the data engineering side;
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, proposes how to re-design infrastructure for greater scalability;
- Develop, construct, test, and maintain data pipelines and architectures such as databases and large-scale processing systems within the constraints of existing but evolving processes and technologies;
- Transform data into formats that can be easily analyzed by developing, maintaining, and testing infrastructures for data generation;
- Prepare data for prescriptive and predictive modeling;
- Provide Subject Matter Expertise to (military and civilian) staff within HQ SACT or the NATO Enterprise and develop proofs of concept, as directed;
- Work in tandem with data scientists and software engineers;
- Select from existing data sources and prepare data to be used by data science models;
- Improve data quality and efficiency;
- Support evaluation of operational requirements and objectives;
- Interpret trends and patterns and support building of algorithms and prototypes;
- Support educational efforts and training development related to data, AI, or digital literacy;
- Remain up-to-date with new developments in Data Engineering and Data Architectures to bring innovative ideas into implementation;
- Support building a data-driven culture that uses data and analytics to generate insights, improve decision making at all levels, inform strategy and policy decisions, and improve performance;
- Perform additional tasks as required by the COTR related to the LABOR category.
Essential Skills/Qualifications:
- A Bachelor or Master's degree from an accredited university in Computer Science, IT, Software or Computer Engineering, Data Science, Applied Mathematics, Physics, Statistics, or a related field
- Experience with advanced level SQL, including query optimization, complex joins, development of stored procedures, user-defined functions, and working with Analytic Functions within the last 3 years
- Proficient in at least one data manipulation language such as Python, Scala, R, etc.
- Ability to develop ETL processes for batch and streaming data with proficiency in tools and technologies such as Apache Spark, Apache Airflow, Pentaho Data Integration, SQL Server Integration Service
- Advanced knowledge of relational database architecture, including design of OLAP and OLTP databases is required. Must have experience working with at least one Data Warehouse schemas – such as Star or Snowflake
- Ability to work with large datasets
- Ability to work in cloud environments to develop scalable data pipelines highly recommended
- Working experience in an international environment with both military and civilian elements
- Understanding of the NATO organization and its functions
- Active National or NATO Secret (or higher) security clearance
Desired Qualifications
- Knowledge of NoSQL databases such as MongoDB, Cosmo DB recommended but not mandatory
- Skills in Cloud infrastructure and technologies such as Google Cloud Compute, AWS, Azure Data Factory, distributed computing will be highly advantageous
- Working experience with geospatial data structures such as raster and vector-based data is recommended
- Ability to collect and document project requirements, and to translate the requirements to technical solutions, including working in an agile environment to implement complex database projects is highly desirable
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