As a Senior Data Engineer at Kharon, you will report to the Associate Director of Data Engineering and play a critical role in driving the evolution of our intelligence platform's data infrastructure. You will help build large-scale distributed automated data processing systems and data lakes, optimizing for both computational and storage efficiency on AWS Databricks.

Your day-to-day responsibilities will include creating data pipelines, infrastructure, and overall workflow orchestration to pull data from a diverse set of global data sources into the Kharon Data Lake. You will build systems to track, monitor, and validate the quality of data coming in or going out of the platform, ensuring the high precision that our clients expect.

Collaboration is a core part of the role; you will work closely with other engineers, architects, and data scientists to implement scalable solutions to complex data problems. You will interact and develop with internal and external APIs, and collaborate with product and business teams to define novel and critical metrics. You will be expected to follow good engineering practices like writing clean documentation, creating system diagrams, and implementing unit/validation tests, taking full responsibility for the development, deployment, adoption monitoring, and maintenance of the systems you build.

To be competitive for the Senior Data Engineer position, you should possess a strong blend of software engineering fundamentals and modern data platform experience.

Must-Have Qualifications

• 6+ years of experience in software or data engineering, preferably with a BS/MS in Computer Science, Engineering, or a related field.
• Strong programming skills in Python, with hands-on experience using Pandas, PySpark, and Notebook environments.
• Deep SQL knowledge and extensive experience working with relational databases, including schema design, access patterns, and query performance optimization.
• Pipeline technologies experience, specifically setting up infrastructure using tools like AWS Glue, Airflow, Kafka, or cloud equivalents.
• Data warehousing experience with modern platforms such as Databricks or Snowflake.
• Container-based deployment experience using Docker and Kubernetes.
• Proven experience taking a complex data project from inception and design through to production deployment.
• Strong verbal and written communication skills, with the ability to explain technical concepts to non-technical stakeholders.

Nice-to-Have Qualifications

• Experience working with or data modeling for graph databases like Neo4J or Amazon Neptune.
• API development experience using frameworks like FastAPI, Flask, or Spring Boot.
• Understanding of Elasticsearch data and query modeling.
• A demonstrated interest or prior experience in Geopolitics, Sanction Compliance, or Financial Risk.

Q: What is the hybrid work policy for the Data Engineer role? A: This role is based out of the Denver, Colorado office and requires in-office attendance 3 days a week. It offers a collaborative environment where you can work directly with team members on-site.

Q: How technical are the coding challenges? A: The coding challenges are completed in Python and are designed to test practical data transformation skills. They are not highly complex algorithmic (LeetCode-style) puzzles, but rather focus on how cleanly you write code, how you transform data structures, and how effectively you communicate your solution.

Q: What databases and storage technologies does Kharon use? A: The core data lake is built on AWS Databricks. The team also works with relational databases, and utilizes specialized technologies like Neo4J for graph data modeling and Elasticsearch for low-latency search applications.

Q: What is the typical timeline for the interview process? A: The entire process—from the initial recruiter screen to the final offer—typically takes between 3 to 4 weeks, depending on candidate and interviewer scheduling.

• Prioritize Clean Code over Clever Code: During the Python challenges, write readable, maintainable code. Use descriptive variable names, handle potential edge cases (like null values or missing keys), and structure your logic clearly.
• Explain Your Trade-offs: When discussing system design and technical use cases, always explain the "why" behind your choices. If you choose Databricks over Snowflake, or a relational schema over a graph database, clearly articulate the trade-offs in performance, cost, and complexity.
• Showcase Your End-to-End Ownership: Kharon values engineers who can take a project from design to production. Highlight past experiences where you not only wrote the ETL code but also set up the Airflow orchestration, configured the Docker containers, and established the data quality monitoring.

• Align with the Mission: Familiarize yourself with Kharon's product offerings before your interview. Understanding how our intelligence platform helps clients navigate sanctions and financial crime risk will help you ground your technical answers in our actual business context.

The Data Engineer and Senior Data Engineer roles at Kharon offer an exceptional opportunity to build highly performant, scalable data systems that directly impact global security and risk management. By designing resilient pipelines, optimizing data lakes on AWS Databricks, and implementing robust data quality frameworks, you will play a foundational role in powering our intelligence platform.

To prepare effectively, focus on solidifying your Python data transformation skills, reviewing distributed system design principles, and practicing how you communicate your technical decisions. The Kharon engineering team highly values practical execution, clear communication, and a strong sense of technical ownership.

The salary range listed above reflects the base compensation for the Data Engineer and Senior Data Engineer positions in Denver, CO. When evaluating your overall offer, keep in mind that Kharon also provides a comprehensive benefits package, including fully sponsored medical, dental, and vision insurance, an FSA program, and a 401k match with immediate vesting.

For more detailed interview insights, platform overviews, and preparation resources, you can explore additional candidate experiences on Dataford. Good luck with your preparation—you have all the tools needed to succeed!