Data Engineer

We are seeking a Data Engineer to support a program in Honolulu, HI. As a Data Engineer, you will play a crucial role in designing, developing, and maintaining our Advana data infrastructure, pipelines and systems. Proficiency in ETL, Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks is crucial for ensuring efficient data ingest, processing and analysis. You will develop and manage ETL processes and data pipelines across various government platforms, working with a wide range of data types.

What you will do

• Design, develop, and implement end-to-end data pipelines, utilizing ETL processes and technologies such as Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks.
• Create and optimize data pipelines from scratch, ensuring scalability, reliability, and high-performance processing.
• Perform data cleansing, data integration, and data quality assurance activities to maintain the accuracy and integrity of large datasets.
• Leverage big data technologies to efficiently process and analyze large datasets, particularly those encountered in a federal agency.
• Troubleshoot data-related problems and provide innovative solutions to address complex data challenges.
• Implement and enforce data governance policies and procedures, ensuring compliance with regulatory requirements and industry best practices.
• Work closely with cross-functional teams to understand data requirements and design optimal data models and architectures.
• Collaborate with data scientists, analysts, and stakeholders to provide timely and accurate data insights and support decision-making processes.
• Maintain documentation for software applications, workflows, and processes.
• Stay updated with emerging trends and advancements in data engineering and recommend suitable tools and technologies for continuous improvement.

What you need to have

Bachelor's Degree and 0 to 2 years of experience; 6 to 8 years with no degree

• Clearance:TS/SCI clearance
• 1+ years of Python experience including developing, running, packaging, and testing Python scripts
• Experience with distributed version control systems (VCS)
• Experience with the entire ETL/ELT pipeline, including data ingestion, data normalization, data preparation, and database design
• Experience with conducting exploratory data analysis to communicate qualitative and quantitative findings to analysts
• Experience processing and fusing structured and unstructured data
• Experience with data engineering projects supporting data science and AI/ML workloads
• Experience creating solutions within a collaborative, cross-functional team environment in team sprint cycles
• Bachelor's degree

What we'd like you to have

• Experience with using Palantir products for data manipulation, correlation, and visualization
• Experience with AWS or other cloud computing services
• Experience with Kafka and NiFi development
• Experience with containerization tools, including Docker and Kubernetes
• TS/SCI with Counterintelligence Polygraph