Data Engineer

Koch Engineered Solutions is seeking a Data Engineer to join its Information Technology capability and support business transformation through technology. The role delivers and maintains reliable, scalable data products for analytics, reporting, and AI solutions; builds ELT pipelines; integrates complex source data; and partners with stakeholders to ensure accurate, production-ready solutions.

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 systems
• Entity resolution
• Data reconciliation
• Python
• Data engineering automation
• Data orchestration
• Data application development
• Data product design
• AI/ML
• LLM integration
• 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

• Engineered solutions for industrial construction and process industries
• Wichita, Kansas, USA
• http://www.kochengineeredsolutions.com/
• Founded in 1945
• 1001-5000 employees

Qualifications

• 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

• Data Pipeline Engineering, SQL, Snowflake, Redshift, BigQuery, Databricks, dbt, Git, CI/CD, Dimensional Data Modeling, Python, Data Integration and Reconciliation

Experience

• 3+ years