Design and implement robust, scalable data pipelines using modern data engineering frameworks.
Build and manage ETL/ELT processes, data lakes, and data warehouses.
Ensure high performance and availability of enterprise data platforms.
Collaborate with data scientists and business analysts to deliver analytics-ready data.
Support data governance, quality, and security compliance.
Maintain presence on the program for a minimum of one year.
Commitments
This Position is a hybrid work environment / 95% Remote - Candidate must live within 2 hours of a government Facility.Maintain presence on the program for a minimum of one year.
Not Met Priorities
What still needs stronger evidence
Requirements
The ideal candidate must have hands-on experience with data integration frameworks, data modeling, and distributed data processing, along with a Databricks and/or Palantir certification.
7+ years of data engineering experience in production environments.
Strong understanding of cloud-based data platforms (AWS, Azure, or GCP).
Demonstrated hands-on coding experience in building and deploying data pipelines.
Preferred Skills
The ideal candidate must have hands-on experience with data integration frameworks, data modeling, and distributed data processing, along with a Databricks and/or Palantir certification.
Experience with Delta Lake, Apache Airflow, or Kafka.
Familiarity with data privacy and compliance frameworks (e.g., GDPR, HIPAA).
Education
(Not required)
– Bachelor’s degree in Science, Math, Engineering, or Information Systems.
Job Summary We are hiring an experienced Data Engineer to architect, build, and optimize scalable data pipelines and analytics solutions. The ideal candidate must have hands-on experience with data integration frameworks, data modeling, and distributed data processing, along with a Databricks and/or Palantir certification. This Position is a hybrid work environment / 95% Remote - Candidate must live within 2 hours of a government Facility. Key Responsibilities
Design and implement robust, scalable data pipelines using modern data engineering frameworks. Build and manage ETL/ELT processes, data lakes, and data warehouses. Ensure high performance and availability of enterprise data platforms. Collaborate with data scientists and business analysts to deliver analytics-ready data. Support data governance, quality, and security compliance. Maintain presence on the program for a minimum of one year. Minimum Qualifications
Bachelor’s degree in Science, Math, Engineering, or Information Systems. 7+ years of data engineering experience in production environments. Databricks and/or Palantir certification (required). Proficient in Python, SQL, and Spark. Strong understanding of cloud-based data platforms (AWS, Azure, or GCP). Demonstrated hands-on coding experience in building and deploying data pipelines. Preferred Qualifications
Experience with Delta Lake, Apache Airflow, or Kafka. Familiarity with data privacy and compliance frameworks (e.g., GDPR, HIPAA).
Potomac Management Solutions, LLC
•
Washington, DC