Data Engineer
About The Position
The Data Engineer will design, develop, and maintain scalable data pipelines and analytics workflows supporting large scale enterprise data processing and modernization efforts. This role will leverage cloud-based data analytics platforms, including Databricks and distributed computing technologies, to build reliable, efficient, and secure data solutions that support analytics, reporting, automation, and operational needs. The ideal candidate will have experience working with large and complex datasets, developing modern ETL/ELT workflows, and supporting cloud-native data environments. This role will collaborate closely with analytics, engineering, DevOps, and business teams to support data-driven decision making and enterprise data initiatives.
Requirements
- Experience working with cloud-based data analytics platforms, specifically Databricks or similar technologies
- Strong programming experience in Python
- Strong programming experience in PySpark
- Strong programming experience in SQL
- Experience building distributed data processing pipelines
- Strong understanding of ETL/ELT pipeline development and data transformation processes
- Experience working with large and complex datasets
- Experience supporting cloud-native or modernized data environments
- Strong analytical, troubleshooting, and problem-solving skills
- Experience collaborating within cross-functional Agile teams
- Excellent written and verbal communication skills
- US work authorization required and ability to obtain and maintain a Public Trust clearance, which may include fingerprinting
Nice To Haves
- Experience implementing data lake or lakehouse architectures
- Experience working within AWS, Azure, or Google Cloud Platform environments
- Experience with workflow orchestration and automation tools
- Experience supporting federal, healthcare, public sector, or highly regulated environments preferred
- Familiarity with AI/ML data workflows or large language model integrations is a plus
Responsibilities
- Design and implement scalable data pipelines for ingesting, transforming, and processing large datasets
- Develop ETL/ELT workflows supporting enterprise data integration and analytics initiatives
- Build and maintain data processing workflows using Databricks and distributed computing technologies
- Develop data transformation and analytics solutions using Python, PySpark, and SQL
- Ensure data quality, consistency, integrity, and governance across systems and workflows
- Optimize performance of data pipelines and large-scale data processing workloads
- Collaborate with analytics, engineering, DevOps, and business teams to support data platform operations and modernization efforts
- Maintain documentation for data architecture, data models, and pipeline processes
- Support secure handling and management of sensitive or regulated data
- Contribute to automation and AI-enabled data workflow initiatives where applicable
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
