Data Scientist

Wyetech is seeking an experienced Data Scientist to support the development, enhancement, and maintenance of enterprise data processing capabilities within a mission-critical Intelligence Community cloud computing environment.

The selected candidate will work closely with Government stakeholders and technical teams to identify requirements for new system capabilities, extend and maintain bulk data pipelines, and enhance multiple applications operating within the customer's cloud infrastructure.

The ideal candidate possesses extensive experience with Python, Spark, PySpark, ETL development, data modeling, SQL databases, and large-scale data processing
, along with the ability to transform complex structured and unstructured datasets into reliable, accessible, and actionable information.

This position requires strong analytical capabilities, hands‑on data engineering experience, and the ability to collaborate with customers and integration partners in an Agile development environment.

• Design, develop, maintain, and enhance large-scale data processing capabilities using Python, Apache Spark, and PySpark.

• Support the development and optimization of bulk data pipelines within enterprise cloud computing environments.

• Process, analyze, and transform complex datasets to support mission-critical applications and analytical requirements.

• Develop scalable data processing solutions capable of handling structured and unstructured information.

• Perform extensive data reviews and data quality analyses to identify inconsistencies, anomalies, and processing issues.

• Apply data modeling and transformation techniques to improve data accessibility, consistency, and usability.

• Support the development of new system capabilities and enhancements to existing cloud‑based applications.

• Collaborate with engineering teams to troubleshoot data processing issues and improve pipeline reliability.

• Design, develop, implement, and maintain Extract, Transform, Load (ETL) processes supporting enterprise data integration.

• Perform data mapping, extraction, transformation, and loading across multiple data sources.

• Integrate disparate structured and unstructured data formats into enriched, query‑friendly structured datasets.

• Develop indexed data files that support efficient querying, reporting, and analytical processing.

• Process and transform XML, JSON, and other supported data formats.

• Develop and maintain source‑to‑target mappings, data dictionaries, and ETL design documentation.

• Identify and resolve data integration challenges, transformation errors, and data quality issues.

• Support ongoing maintenance, enhancement, and optimization of bulk data pipelines.

• Collaborate with integration partners to ensure accurate data ingestion, transformation, and delivery.

• Develop and execute SQL queries to retrieve, manipulate, validate, and analyze data.

• Work with relational database technologies, including SQL, MySQL, and PostgreSQL.

• Support data modeling and analytical development using notebooks and integrated development environments.

• Utilize Visual Studio and applicable development tools to support data processing and analytical workflows.

• Develop and maintain structured datasets optimized for analytical queries and reporting.

• Perform data validation, reconciliation, and quality assurance activities.

• Identify opportunities to improve database queries, data structures, and processing efficiency.

• Support the integration of relational database information into enterprise data pipelines.

• Process and convert operating system logs and application data logs into actionable reports,…