56 applicants

Company

Original Job Post

ManTech · 23 hours ago

Data Engineer

Herndon, VA

Full-time

Hybrid

Senior Level

5+ years exp

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Responsibilities

Analyze large and disparate data sets to understand their structures, assess suitability for use in developing and operating predictive models and other AI solutions, and recommend updates to better support this use.

Develop large volume data sets sourced from multitude of relational tables to allow data analysts and scientists to construct training sets for machine learning models and recurring reports and dashboards.

Work with data scientists, machine learning engineers, and architects to design and implement data structures, data management, and data governance for analytics, data science, and AI-based systems.

Engage in data analysis, problem solving, investigation, and creative thinking with large to massive data sets to support a variety of analytic scenarios.

Create robust and resilient data pipelines to connect data sources to analytic and AI tools and solutions.

Respond to data queries and analysis requests as needed to support analytic and AI projects and solution development. Create and publish regularly scheduled and/or ad hoc reports as needed.

Collaborate with client to assist in creating, managing, and optimizing Extract, Transform, and Load (ETL) jobs and workflows.

Assist with the implementation of data migration/pipelines from on-prem to cloud storage platforms.

Contribute data engineering to solution accelerators, prototypes, proofs-of-concept, and methods for use in client engagements.

Participate in design thinking or other solution-based methods to solve problems consisting of various qualitative activities that support the generation of insightful, human-centered and impactful design solutions.

Perform knowledge elicitation from client of business problem details relative to data requirements and incorporate that knowledge into data structures, management, governance, and processes.

Identify AI and data science challenges in non-AI projects to enhance the projects’ capabilities.

Support collection of data needed for analytic and AI solutions.

Participate in solution development through whiteboarding sessions with clients, partners, and coworkers.

Contribute to solutions with data storage, data structures, data manipulation tasks, data governance, or other technical challenges related to data engineering.

Communicate findings to diverse technical and non-technical stakeholders and engage client to distill complex technical language.

Qualification

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Cloud Providers AWSCloud Providers OracleCloud Providers IBMCloud Providers AzureCloud Providers GCPDatabase Search QueriesSQLData ExtractionData TransformationData NormalizationData EnrichmentData CorrelationData StorageAPI DevelopmentAPI IntegrationETL PipelineData ModelingRelational DatabasesNon-Relational DatabasesFile Formats JSONFile Formats XMLProgrammingScriptingProblem-SolvingData AnalysisCI/CD Tools KnowledgeInitiativeCommunicationCollaboration

Required

Bachelor’s degree in computer science, Engineering, or Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, or related field and 7 years of relevant experience OR a Master's degree and 5 years of experience or equivalent experience.

In depth knowledge with one or more cloud providers (e.g., AWS, Oracle, IBM, Azure and GCP) and experience working across environments and on premise.

Strong experience constructing and performing complex database search queries.

Proficiency in SQL.

Knowledge of data extraction, transformation, normalization, enrichment, correlation, storage, and API development and integration.

Strong knowledge of the full data ETL pipeline, including data retrieval

Strong experience with data modeling.

Experience with relational and non-relational databases.

Experience working with various file formats such as JSON, XML or similar.

Experience with programming or scripting

Effective research, analytical and problem-solving skills