Senior Data Engineer

ESS Companies

. Own data pipelines, including automated replication and ingestion into the warehouse .

Posted 9/29/2026full-timeColumbia • Missouri • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data engineering, including building and maintaining data pipelines, cloud warehouse architecture, and dimensional modeling. Proficient in translating business needs into scalable data solutions while ensuring data quality and reporting accuracy.

Highest-signal resume keywords

Data Engineering FundamentalsSQL and Python ProficiencyCloud Data Warehouse ExperienceDimensional Modeling ExpertiseData Pipeline Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentSQLPythonDimensional ModelingData Transformation FrameworksELT/Data Replication ToolsCloud Data WarehouseCost OptimizationData Quality ChecksData Lineage Management

Soft Skills

Independent Decision-MakingCollaboration with Stakeholders

Tools & Technologies

BigQuerySnowflakeRedshiftDbtFivetranGoogle Cloud PlatformCloud RunCloud SQL/PostgreSQLPub/SubCloud Scheduler

Industry Keywords

ConstructionEngineeringOperations

Tech Stack

Tools & technologies

Amazon RedshiftBigQueryCloudERPGoogle Cloud PlatformPostgresPythonSQL

About the role

Key responsibilities & impact

Own data pipelines, including automated replication and ingestion into the warehouse
Monitor pipeline performance, troubleshoot failures, handle schema changes, and add new data sources
Maintain and evolve cloud warehouse architecture
Define layering, naming conventions, performance standards, and cost-efficiency practices
Ensure scalability across multiple subsidiaries
Design and maintain dimensional data models, including facts and dimensions
Partner with Finance, HR, and Operations leaders to translate business needs into data structures
Build models supporting accurate, decision-ready reporting
Implement testing, documentation, and data-quality checks
Maintain clear data lineage and reporting transparency
Ensure stakeholders trust reporting accuracy
Own the data platform and make independent architectural and operational decisions

Requirements

What you’ll need

Strong data engineering fundamentals with clean, maintainable SQL and Python
Experience building and operating production data pipelines
Hands-on experience with a cloud data warehouse; BigQuery preferred, with Snowflake, Redshift, or similar acceptable
Experience with transformation frameworks; dbt strongly preferred
Understanding of layered data architecture (raw → staging → modeled)
Solid understanding of dimensional modeling, including facts, dimensions, and star schema design
Experience with ELT/data replication tools such as Fivetran
Ability to translate business needs into scalable data solutions
Comfortable owning decisions and operating independently
Experience with Google Cloud Platform, including Cloud Run, Cloud SQL/PostgreSQL, Pub/Sub, Cloud Scheduler, and Secret Manager
Experience integrating ERP systems such as Viewpoint Vista and HCM platforms such as 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