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# Senior Data Engineer

- **Company:** Leidos Holdings, Inc.
- **Location:** Seattle, WA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $73,450.0 - $132,775.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Extract Transform Load (ETL), Apache Hive, Python (Programming Language), Performance Tuning, Data Streaming, Data Processing, Google Cloud, Data Ingestion, Apache Spark, Pyspark, Integration Frameworks, Apache Kafka, Data Management, Data Pipelines
- **Published:** October 4, 2026
- **Apply:** https://www.careerjet.com/jobad/usb68974adf3ee9ecf06a0050a726ec481

## About the Role

* Strong Functional Knowledge in Retail (Search & Personalization) Added advantage.
 * Strong experience with large-scale GCP Data Engineering solutions.
 * Hands-on experience with Airflow DAG development and support
 * Experience building and optimizing Spark/PySpark data pipelines.
 * Exposure to Hive-based data processing and Kafka-driven ingestion frameworks.
 * Experience supporting analytics, personalization, recommendation, or search platforms is highly desirable

## Description

Must Have Technical/Functional Skills
Must Have Technical/Functional Skills

 * Google Cloud Platform (GCP)
 * PySpark
 * Python
 * Airflow
 * Hive
 * Kafka

Data Pipeline Development, Enhancement & Maintenance

 * Design, build, and maintain scalable ETL/ELT pipelines.
 * Automate data ingestion from multiple data sources.
 * Ensure reliable, high-performance, and scalable data movement.
 * Develop and optimize PySpark-based data processing frameworks.
 * Build and manage Airflow workflows and orchestration pipelines.
 * Work with Hive and Kafka-based batch and streaming data solutions.
 * Implement data quality, monitoring, governance, and operational controls.
 * Support production incidents, performance tuning, and continuous improvement initiatives

Roles & Responsibilities

 * The Data Engineer will be responsible for designing, building, governing, and optimizing data platforms, pipelines, and integrations to ensure secure, reliable, and scalable data availability for analytics, reporting, AI/ML, and business operations.