5-7 years of experience in data engineering or related field
Proficient in SQL and Python for data management
Experience with building production data pipelines
Hands-on knowledge of cloud data warehouses, preferably BigQuery
Familiarity with dbt for transformation frameworks
Strong understanding of dimensional modeling techniques
Ability to communicate effectively with non-technical stakeholders
Responsibilities
Own and manage data pipelines for warehouse ingestion
Monitor and troubleshoot performance issues and failures
Maintain and evolve the cloud architecture for scalability
Design and maintain dimensional data models
Collaborate with business leaders to translate needs into data structures
Implement data quality checks and ensure data reliability
Build documentation and maintain clear data lineage
Benefits
Opportunity for ownership over a broad scope of duties
Collaborative environment with direct impact on decision-making
Focus on practical data solutions that serve business needs
Potential for career growth in a dynamic and evolving role
Full Job Description
This is an on-site role based in Columbia, MO or Kansas City, MO. Candidates must be within driving distance and able to work in-office regularly. Remote work is not available for this position.
It's a broad role with real ownership, which is both the appeal and the challenge: there isn't a senior engineer above you reviewing every decision. We're looking for someone ready to own the whole platform and confident enough to ask questions when needed.
What you'll do:
Own the data pipelines
Manage automated replication and ingestion into the warehouse
Monitor performance, troubleshoot failures, and handle schema changes
Add new data sources as business needs evolve
Own the platform architecture
Maintain and evolve the cloud warehouse architecture
Define layering, naming conventions, performance standards, and cost efficiency
Ensure scalability across multiple subsidiaries
Own the data modeling
Design and maintain dimensional models (facts and dimensions)
Partner directly with Finance, HR, and Operations leaders to translate business needs into data structures
Build models that support accurate, decision-ready reporting
Ensure data trust and reliability
Build in testing, documentation, and data quality checks
Maintain clear data lineage and transparency
Ensure stakeholders trust the accuracy of reporting
What we're looking for
Strong data engineering fundamentals - clean, maintainable SQL and Python
Experience building and operating production data pipelines
Hands-on experience with a cloud data warehouse (BigQuery preferred; Snowflake, Redshift, or similar acceptable)
Experience with transformation frameworks (dbt strongly preferred) and layered data architecture (raw → staging → modeled)
Solid understanding of dimensional modeling (facts vs. dimensions, star schema design)
Experience with ELT / data replication tools (Fivetran or similar)
Ability to partner with non-technical stakeholders and translate business needs into scalable data solutions
Comfortable owning decisions and operating independently
Nice to have
Experience with Google Cloud Platform (Cloud Run, Cloud SQL/PostgreSQL, Pub/Sub, Cloud Scheduler, Secret Manager)
Experience integrating ERP systems (Viewpoint Vista or similar) and HCM platforms (Workday)
Familiarity with CI/CD-driven data workflows and version-controlled transformations
Experience managing warehouse cost optimization
Background in construction, engineering, or operations-heavy industries
Reminders:
This is strictly an on-site role
Must be located within driving distance of Columbia, MO or Kansas City, MO
No remote or hybrid work options available
Who Thrives Here: The person who does well here likes owning the whole thing rather than a corner of it, cares more about whether the numbers are right than whether the pipeline is clever, and would rather ship a model the finance team actually uses than a perfect one nobody asked for. You're comfortable being the person who knows how the data fits together, and you treat "the business owner doesn't quite know what they want yet" as part of the job rather than a blocker.
