Senior Cloud Data Engineer - Remote (Secret Clearance)

Advantech GSE; United States; Remote; USD 140,000 - 200,000; Full time

Job summary

Advantech GS Enterprises is seeking a Sr. Data Cloud Engineer to support the DISA NEXUS program at Fort Meade.

The role focuses on designing, building, and maintaining scalable cloud-based data solutions to enable enterprise modernization and mission-critical analytics within secure DoD environments. Ideal candidates will have strong PySpark, Spark SQL, Python, and SQL experience, with hands-on work in Azure and/or AWS cloud services.

Qualifications

• Active Secret Clearance required.
• 10+ years designing and operating scalable, production-grade data pipelines.
• Strong PySpark and Spark SQL for large-scale transformations.
• Advanced Python and SQL for data querying, automation, and analysis.
• Experience with Azure Synapse Analytics and/or Databricks.

Responsibilities

• Design, develop, and maintain scalable cloud-based ETL/ELT pipelines using Azure Synapse Analytics, Databricks, AWS Glue, and related technologies.
• Build and optimize large-scale data transformations with PySpark and Spark SQL.
• Develop data ingestion frameworks for structured and unstructured data.
• Implement full and incremental data loading strategies including CDC and rerunnable pipelines.
• Design and maintain data lakes, warehouses, and analytics-ready datasets for enterprise reporting.

Skills

PySpark

Spark SQL

Python

SQL

Data pipeline design

Education

Bachelor’s degree in Computer Science, Data Science, Engineering, Information Systems, or related technical field

Tools

Azure Synapse Analytics

Databricks

AWS Glue

Redshift

S3

Job description

Advantech GS Enterprises is seeking a Sr. Data Cloud Engineer to support the DISA NEXUS program at Fort Meade.

The role focuses on designing, building, and maintaining scalable cloud-based data solutions to enable enterprise modernization and mission-critical analytics within secure DoD environments. Ideal candidates will have strong PySpark, Spark SQL, Python, and SQL experience, with hands-on work in Azure and/or AWS cloud services.