Data Engineer

AI overview

Design scalable data pipelines and optimize Spark workloads to support advanced analytics and AI initiatives across major cloud platforms.

Data Engineer

Syntasa is hiring a cleared Data Engineer to design scalable data pipelines, optimize Spark workloads, and deliver high-performance cloud solutions. You’ll be working across all major cloud providers to build cost-efficient, production-ready systems that power advanced analytics and AI initiatives.

Key Responsibilities

• Optimize large-scale data pipelines for ingestion, transformation, and processing.

• Develop robust, reusable code in Python and Spark to support distributed data workflows.

• Manage and tune Spark jobs on cloud-based platforms with Kubernetes orchestration.

• Implement scalable data solutions for storage and retrieval.

• Drive reliability, performance, and cost efficiency across cloud infrastructure.


Required Skills

• Strong Python experience

• Experience with automation of job monitoring, optimization, and debugging at scale

• Experience working with any of the major cloud providers

• Excellent communication skills with the ability to work in cross-functional teams

• TS/SCI w/CI Poly preferred


Desired Skills

• Apache Spark

• Background in building and maintaining CI/CD pipelines

• Knowledge of Kubernetes and containerization

• Experience building dashboards

• Using notebook-based tools such as Jupyter and Databricks

• Knowledge of Scala, SQL and R


Cleared Secret but TS/SCI w/CI Poly preferred

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