Data Engineer

Koch Engineered Solutions (KES) is a network of businesses focused on improving operational efficiency, safety, waste reduction, and emissions through domain expertise. The Data Engineer will deliver and maintain reliable, scalable data products supporting analytics, reporting, and AI solutions, while partnering with stakeholders and Data Architects to integrate complex data sources and improve the modern data platform.

Responsibilities

• Own the delivery and ongoing success of data products, ensuring they solve the intended business problem and remain reliable, usable, and maintainable in production
• Build and maintain ELT pipelines across staging, intermediate, and mart layers using modular engineering practices, automated testing, and production-ready deployment processes
• Engage directly with business stakeholders, including cost accountants, project managers, and analysts, to understand their processes, validate business logic, and ensure data models accurately represent real-world operations
• Integrate data from diverse and sometimes complex source systems, including multiple ERPs, APIs, file-based feeds, and cloud services, making deliberate decisions about entity resolution and cross-system reconciliation
• Structure data products to be AI-ready through semantic clarity, consistent naming, documented lineage, and quality sufficient for both human analysts and AI/LLM consumption
• Apply AI-assisted engineering tools, such as Claude Code and Snowflake Cortex, to accelerate delivery, improve code quality, and identify opportunities to embed AI capabilities into data products
• Establish risk-based data quality controls that validate critical business rules, detect upstream issues early, and prevent unreliable data from reaching consumers
• Contribute to platform reliability by incorporating monitoring, alerting, automation, and operational support into delivered solutions
• Participate in legacy platform migration, transitioning workloads to the modern data stack while preserving data integrity and business continuity
• Strengthen team capability through code reviews, pairing, documentation, and reusable engineering patterns that improve consistency and reduce key-person dependencies

Preferred

• 3+ years of experience building data pipelines in a cloud data warehouse environment
• Experience using AI-assisted development tools to improve engineering productivity and solution quality
• Experience integrating data across multiple ERPs or source systems, including entity resolution and reconciliation
• Python experience supporting data engineering automation, orchestration, or data applications
• Experience designing data products for analytics, AI/ML, or LLM consumption
• Experience with Power BI data modeling, semantic layer design, or business-facing analytics solutions
• 3+ years of experience building data pipelines in a cloud data warehouse environment.
• AI-assisted development tools
• Data integration
• ERP integration
• Source system integration
• Entity resolution
• Data reconciliation
• Python
• Data engineering automation
• Orchestration
• Data applications
• Data product design
• AI/ML
• LLM data consumption
• Power BI
• Data modeling
• Semantic layer design
• Business-facing analytics

Benefits

• Medical
• Dental
• Vision
• Flexible spending accounts
• Health savings accounts
• Life insurance
• ADD
• Disability
• Retirement
• Paid vacation/time off
• Educational assistance
• May also include infertility assistance, paid parental leave and adoption assistance

Company

• Diversified conglomerate acquiring and investing in businesses worldwide
• Wichita, Kansas, USA
• https://www.kochinc.com/
• Founded in 1940
• 10001+ employees

Qualifications

• This position is based in Wichita, KS, and is not eligible for VISA Sponsorship
• Hands-on experience building data pipelines in a cloud data warehouse environment
• SQL skills and experience with cloud data platforms such as Snowflake, Redshift, BigQuery, or Databricks
• Experience using dbt or a comparable transformation framework that supports version control, testing, and modular design
• Working knowledge of cloud services and modern software engineering practices, including Git and CI/CD
• Experience applying dimensional data modeling and translating business processes into scalable data structures
• Experience partnering directly with business stakeholders to define requirements, validate business logic, and ensure data accuracy
• 3+ years of experience building data pipelines in a cloud data warehouse environment
• Experience using AI-assisted development tools to improve engineering productivity and solution quality
• Experience integrating data across multiple ERPs or source systems, including entity resolution and reconciliation
• Python experience supporting data engineering automation, orchestration, or data applications
• Experience designing data products for analytics, AI/ML, or LLM consumption
• Experience with Power BI data modeling, semantic layer design, or business-facing analytics solutions

Required skills

• SQL, Cloud Data Warehousing, Snowflake, Amazon Redshift, Google BigQuery, Databricks, dbt, Git, CI/CD, Dimensional Data Modeling, Data Pipeline Engineering, Python

Experience

• 3+ years