We are K1x. Our platform powers the first fully digital K-1, transforming how alternative investment tax data is extracted, validated, distributed, and analyzed. Trusted by leading institutional investors, fund administrators, and accounting firms, K1x replaces manual, error-prone workflows with scalable, intelligent software. k1x.io
As our platform evolves toward deeper analytics, insights, and AI-driven capabilities, data engineering is becoming a foundational pillar of our product and technology strategy.
About The Role
We are seeking a Data Engineer to design, build, and maintain the data pipelines and infrastructure that power K1x’s machine learning initiatives and future analytics-driven product features.
This role sits at the intersection of Product Engineering, Data, and Machine Learning. You will be responsible for creating reliable, scalable, and high-quality data systems that enable downstream ML models, reporting, and embedded analytics.
What You’ll Do
- Design, build, and maintain scalable data architectures supporting operational, analytical, and ML workloads.
- Contribute to the evolution of K1x’s data lakehouse strategy, including adoption of Snowflake.
- Develop and maintain robust 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 use cases including Power BI.
- Partner with Product, Engineering, and AI teams on data solutions.
Requirements
Who You Are
- 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 with SQL and relational data modeling.
- Experience with cloud-based data platforms (Azure preferred).
- Understanding of data quality, reliability, and monitoring.
- Strong communication and collaboration skills.
It’s Truly a Match If You Have
- An engineering mindset applied to data platforms.
- Passion for building scalable, reliable data foundations.
- Interest in enabling ML and analytics-driven products.
- Experience or familiarity with Snowflake, SQL Server, Azure, and Power BI.
- Comfort balancing near-term delivery with long-term architecture.
Benefits
Data Engineer • Chicago, IL, US
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