Job Summary:

The Data Engineer / ETL Developer is responsible for designing, developing, and maintaining data integration and ETL/ELT solutions to support enterprise analytics platforms. This role involves acquiring, transforming, validating, and integrating data from various government and commercial sources, ensuring high data quality, and supporting automated data pipelines within cloud-based environments.

Responsibilities:
  • Design, develop, test, and maintain ETL/ELT processes and automated data pipelines.
  • Integrate data from APIs, databases, cloud storage, enterprise applications, and external data providers.
  • Support data ingestion, transformation, cleansing, enrichment, and validation processes.
  • Monitor and troubleshoot data workflows, pipeline performance, and data quality issues.
  • Implement automated data quality checks and schema validation routines.
  • Develop and maintain data models, metadata repositories, and data lineage documentation.
  • Support cloud-based data platforms and analytics environments.
  • Collaborate with Data Architects, Data Scientists, and BI Developers to deliver analytics-ready datasets.
  • Develop scripts and automation tools to streamline data movement and processing activities.
  • Support DataOps, CI/CD, and Infrastructure-as-Code initiatives.
  • Ensure compliance with cybersecurity, data governance, and federal data management requirements.
Required Skills & Certifications:
  • Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related field.
  • 3+ years of experience developing ETL/ELT solutions.
  • Proficiency with SQL and relational database platforms.
  • Experience with Python, Spark, or other data processing technologies.
  • Experience developing automated data pipelines in cloud environments.
  • Familiarity with data governance, metadata management, and data quality concepts.
  • Ability to obtain and maintain a Secret Clearance.
Preferred Skills & Certifications:
  • Experience with AWS, Azure, or DoD cloud environments.
  • Experience with Kafka, Kinesis, or real-time data streaming technologies.
  • Knowledge of DataOps practices and CI/CD pipelines.
  • Experience supporting federal or DoD programs.
Special Considerations:
  • Must be able to obtain and maintain a Secret Clearance.
  • Compliance with federal cybersecurity, data governance, and data management requirements.
Scheduling:
  • Standard work schedule with possible adherence to government or program-specific shift patterns.
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