Data Engineer

A U.S.-based company that is developing the largest dataset of global risk and threat indicators and tactical intelligence in the world is looking for a Data Engineer. The engineer will be in charge of developing the latest features and fixing bugs to ensure platform scalability and stability. The company is harnessing the power of AI-powered technology to help security organizations to protect their people, assets, operations, and supply chains. The company has managed to secure $6 mn+ during their Seed round of funding. This will be a long-term position requiring some overlap with the CST time zone.

Job Responsibilities:

• Build, test, and maintain robust ingestion and transformation pipelines
• Monitor the injection of NLP models to extract and augment data from free text sources
• Develop data transformation, validation, and analysis methods to augment the utility and actionability of data
• Mature data models with respect to consumption patterns and performance objectives
• Operationalize data quality and ensure visibility and timely remediation of data quality issues
• Contribute to GIS data architecture strategies, and drive transformation and implementation activities resulting from them 

Job Requirements:

• Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
• At least 5+ years of relevant experience as a data engineer
• A minimum of 5+ years of experience building production-level data pipelines and standing up the platforms to support them
• At least 5+ years of experience implementing and maintaining data warehouses, data models, and performing schema migrations
• Prolific working knowledge of SQL
• Hands-on experience with GIS-enabled data stores
• Demonstrable thought leadership in operationalizing data quality 
• Prior experience delivering production-ready code
• Familiarity with GIS-related libraries such as GeoPandas
• Nice to have experience with JavaScript
• Familiarity with AWS pipeline tools, including step functions
• Strong collaborator across functional areas, including data science, infrastructure, SW development, and product
• Fluent in verbal and written English