Data Engineer

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profile Job Location:

Washington, AR - USA

profile Monthly Salary: Not Disclosed
Posted on: 30+ days ago
Vacancies: 1 Vacancy

Job Summary

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:

  • Bachelors 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).
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 Pala...
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Key Skills

  • Apache Hive
  • S3
  • Hadoop
  • Redshift
  • Spark
  • AWS
  • Apache Pig
  • NoSQL
  • Big Data
  • Data Warehouse
  • Kafka
  • Scala

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