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Data Engineer

1 month ago

Honolulu, Hawaii, United States Input Technology Solutions Full time
Job Overview

Input Technology Solutions is seeking a highly skilled 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 essential for ensuring efficient data ingest, processing, and analysis.

Key Responsibilities
  • 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.
Requirements
  • 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.
Preferred Qualifications
  • 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.