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# Mid Data Engineer

- **Company:** Ignite, LLC
- **Location:** Washington, DC, United States (Remote available)
- **Experience:** Experienced
- **Salary:** $130,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Cloud Computing, Cloud Storage, CompTIA Security+, Databases, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Warehousing, Data Flow Control, Apache Hadoop, Python (Programming Language), SQL Databases, Data Processing, Google Cloud, Azure Data Factory, Snowflake, Apache Spark, Kubernetes, Information Technology, Apache Nifi, Data Pipelines, Databricks
- **Published:** July 23, 2026
- **Apply:** https://jobs.localjobnetwork.com/apply/add/87815296/1

## About the Role

* Expertise in Python, SQL, Spark, andPySpark.

 * Experience with cloud-based ETL services (e.g.AWS Glue, Google Cloud Dataflow, Azure Data Factory).

 * Familiarity with Databricks, Palantir,Snowflake, and data warehousing technologies.

 * Strong understanding of data orchestration and quality processes.

Desired Skills:

 * Experience withDocker/Kubernetes, Hadoop/Spark,NiFi, ELK stackor comparable technologies.

 * Data engineering certification (e.g.Azure, Google, IBM, Palantir).

 * Experience working with federal clients.

Clearance Requirements:

 * U.S. Citizen, Secret or TS/SCI eligible.

Education & Experience:

 * Bachelor's degree in computer science, engineering, mathematics, or related field.

 * 3+years relevant professional experience.

 * Intermediate certifications(Cloud+, GSEC,Security+, SSCP);or advancedcertifications(SecurityX/CASP+, CCNP Security, CISA, CCSP, CISSP).

## Description

* Independently design, build, and maintain end-to-end data pipelinesand core infrastructure.

 * Develop efficient data processing and transformation workflows.

 * Create and maintain data models,schemasandtransformation logic to support analytics requirements.

 * Integrate diverse data sources (APIs, databases, cloud storage) into unified datasets.

 * Implement robust validation, monitoring, and observability processes.

 * Contribute to data governance, security, and automation initiatives.


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