Enterprise Data Engineer
Chantilly, VA
TS/SCI and FSP is Required
$200K to $250K
We are seeking skilled and detail-oriented Data Engineers with expertise in utilizing Python, SQL, and ETL to extract, transform, and load structured and unstructured data from various sources.. The ideal candidate will have a strong background in data engineering and a deep understanding of ETL processes.
Key Responsibilities:
· Write robust and efficient Python and SQL scripts to automate data processing tasks.
· Integrate data from diverse sources, such as databases, APIs, and flat files, into centralized systems.
· Implement data transformations, enrichment, and modeling workflows to ensure data quality and usability.
· Ensure data structures are optimized for performance and scalability.
· Provide technical guidance and support to ensure effective use of Palantir tools across teams.
· Implement data quality checks, validation, and monitoring mechanisms to ensure the accuracy and reliability of datasets.
· Integrate data from diverse sources, such as databases, APIs, and flat files, into centralized systems.
· Ensure proper data transformation and curation to meet business and analytics requirements.
· Maintain and improve data quality, consistency, and accuracy through validation and cleansing processes.
Required Skills:
· 3+ years of experience in data engineering.
· Strong proficiency in scripting and programming with Python.
· Expertise in working with SQL for data querying, transformation, and optimization.
· Experience with data integration from diverse sources such as APIs, relational databases, and file systems.
· Strong analytical and problem-solving skills with attention to detail.
· Excellent communication and teamwork skills to collaborate with technical and business teams.
· Active TS/SCI FSP is required to start. Role is FT on-site in Herndon, VA.
Preferred Skills:
· Bachelor’s degree in Computer Science, Data Engineering, or a related field.
· Hands-on experience with Palantir.
· Experience with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies (e.g., Apache Spark, Hadoop).
· Familiarity with data orchestration tools such as Apache Airflow, Prefect, or similar.