Data Engineer

Kharon•Denver, CO

6d•$120,000 - $160,000•Onsite

About The Position

Operating at the nexus of global security, Kharon is on a mission to revolutionize the current landscape. We take really complex data as it relates to global security and empower our clients to not only understand the risk associated with their potential business relationships but to operationalize that data so that they can make the best and most informed decisions possible. From financial crimes and sanctions to export controls and threat identifications, our tools optimize protection against the types of risks that could otherwise be incredibly dangerous and excessively costly to any business. Serving many of today’s leading global financial and multinational institutions, Kharon products are the most powerful in the space with a precision and depth that is absolutely unparalleled. When you look at any major global crisis event, we’re providing intelligence that’s at the heart of those circumstances. We connect the dots in a way that’s meaningful. Now, we’re experiencing unprecedented growth. As the world continues to evolve in complexity, so too does the demand for our products. Given the significance of our work and the increasing global reliance on our insights, we are looking for a Data Engineer to join us as we work to shape the way businesses perceive and navigate global risks. Reporting to the Associate Director of Data Engineering, the Data Engineer will excel in designing, evaluating, and executing on solutions to open-ended problems through superior analytical skills, resourcefulness, and tenacity. They will be innately curious and have demonstrated an entrepreneurial spirit through academic, professional, or extracurricular experiences. This person should be able to demonstrate their ability to quickly learn new skills and familiarize themselves with new subjects. To the right person, this will be the perfect kind of challenge. Our mission is compelling, our product is powerful, and we’re growing at a rate that makes us unstoppable. If you’re looking to be surrounded by people who will inspire you to think and challenge you to grow then look no further. Our team is made up of some of the most visionary and uncompromising individuals you will ever encounter. We don’t take ourselves seriously but we’re serious about the work we do and there is absolutely no slowing us down.

Requirements

2+ years of experience, not including internships as a software engineer or a data engineer and a strong passion to learn.
BS/MS in Computer Science or equivalent experience in related fields.
Experience in Python, Pandas, PySpark, and Notebooks.
SQL knowledge and experience working with relational databases including schema design, access patterns, query performance optimization, etc.
Experience with data pipeline technologies like AWS Glue, Airflow, Kafka, or other cloud based equivalence.
Experience with ETL and data warehousing like Databricks, Snowflake, or equivalent.
Container-based deployment experience using Docker and Kubernetes.
Strong verbal and written communication skills.

Nice To Haves

Experience working with or data modeling for graph databases like Neo4J, Neptune, etc.
API experience using FastAPI, Flask, Spring Boot or equivalent.
Understanding of elasticsearch data and query modeling is a big plus.
Interests or experience in Geopolitics, Sanction Compliance, or Financial Risk.

Responsibilities

Help build large-scale distributed automated data processing systems and data lakes, while optimizing for both computational and storage efficiency on AWS Databricks.
Create data pipelines, infrastructure, and overall workflow orchestration to pull data from a diverse set of data sources into the Kharon Data Lake.
Build systems to track, monitor and validate the quality of data coming into or going out of Kharon Data Lake.
Collaborate with engineers, architects, and data scientists to implement scalable solutions to solve complex problems.
Interact and develop with internal and external APIs.
Work with product and business teams to define novel and critical metrics for the business.
Follow good engineering practices like documentation, diagrams, and unit/validation tests
Take full responsibilities for the development, deployment, adoption monitoring and maintenance of the data systems and services you build.