About the role

Role Overview

You will design, build, and maintain the data pipelines and infrastructure that power K1x’s machine learning initiatives and future analytics-driven product features. The role sits at the intersection of Product Engineering, Data, and Machine Learning.

Responsibilities

Design, build, and maintain scalable data architectures supporting operational, analytical, and ML workloads
Help evolve K1x’s data lakehouse strategy, including adoption of Snowflake
Develop and maintain ETL/ELT pipelines for large-scale data processing
Implement data quality checks, validation, and monitoring
Enable machine learning workflows with clean, well-structured datasets
Support analytics and reporting, including Power BI
Collaborate with Product, Engineering, and AI teams on data solutions

Requirements

4–8+ years of experience in data engineering or backend engineering with a data focus
Strong experience building data pipelines and ETL/ELT workflows
Proficiency in SQL and relational data modeling
Experience with cloud-based data platforms (preferably Azure)
Understanding of data quality, reliability, and monitoring
Strong communication and collaboration skills

Nice to Have / If You Have It

Engineering mindset focused on data platforms and scalable, reliable foundations
Interest in enabling ML and analytics-driven products
Familiarity with Snowflake, SQL Server, Azure, and Power BI

About K1X, Inc.

K1X, Inc. (K1x) provides a fully digital K-1 platform that extracts, validates, distributes, and analyzes alternative investment tax data. The company serves institutional investors, fund administrators, and accounting firms, replacing manual and error-prone workflows with scalable software. As the platform evolves toward advanced analytics and AI capabilities, data engineering underpins its product and technology strategy.

Data Engineer

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