Data Engineer

Baker Group • Ankeny, IA

64d

About The Position

The Data Engineer designs, builds, and maintains the data pipelines and infrastructure that power Baker Group’s Microsoft Fabric data warehouse, which serves as the organization’s single source of truth. The role owns ingestion, transformation, and orchestration of data from internal systems—including ERP, HRIS, MRP, and other structured sources—into governed, reliable data products for analysts and developers. It ensures data supports traditional reporting as well as emerging AI and machine-learning use cases. The role curates core datasets across employees, finance, construction and manufacturing projects, and service, and partners with Data Scientist, Data Analyst, and Software Development roles to provide trustworthy, well-structured data for downstream use.

The position also manages data models, quality, governance, infrastructure, and documentation; collaborates with business-system owners and technical teams; resolves pipeline and data-quality issues; and evaluates data engineering tools and practices. Other duties may be required and assigned.

Requirements

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or another relevant quantitative field.
• Three to five years of experience in data engineering, ETL/ELT development, or a related field.
• Proficiency with SQL and database technologies for data extraction, transformation, and loading.
• Experience with Microsoft Fabric, Azure Data Factory, or similar cloud ETL/orchestration tools.
• Experience with medallion architecture and modern data warehousing patterns.
• Experience with a programming language such as Python, PySpark, or T-SQL for data transformation.
• Familiarity with data modeling techniques, including dimensional modeling and star schemas.
• Understanding of data governance, data quality, and metadata management practices.
• Strong analytical and troubleshooting skills to diagnose and resolve complex pipeline and data-quality issues.
• Excellent time and project management skills, including prioritizing multiple pipeline and infrastructure projects.
• Strong communication skills and ability to explain technical data structures to non-technical stakeholders.
• Strong collaboration skills, particularly with the Data Scientist, Data Analysts, and business-system owners.
• Ability to focus on complex technical problems and work independently with minimal supervision.
• Ability to work in a fast-paced environment and adapt to changing business priorities.
• Meticulous attention to detail and commitment to reliable, well-documented data infrastructure.

Nice To Haves

• Experience preparing data for AI/ML consumption, such as vector embeddings or RAG architectures.
• Business acumen and understanding of construction or related industries.
• Relevant certifications, such as Microsoft Certified: Fabric Data Engineer Associate, Azure Data Engineer Associate, or similar cloud-platform certifications.

Responsibilities

• Design, build, and maintain ETL/ELT pipelines that ingest enterprise-system data into Microsoft Fabric.
• Architect and maintain the Fabric medallion Lakehouse structure, including bronze, silver, and gold layers.
• Develop and implement data infrastructure best practices, including Development/Test/Production environments and Git version control.
• Own pipeline orchestration, scheduling, and monitoring to ensure reliable, timely, and accurate data availability.
• Curate and maintain core datasets across employee, finance, project, service, and manufacturing domains.
• Establish and enforce data quality, validation, and reconciliation processes across pipelines.
• Design and manage data models, schemas, and semantic layers to support reporting and data science work.
• Define and maintain data ontologies and canonical business definitions to ensure consistent meaning across systems and consumers.
• Prepare and structure data for AI and machine-learning use cases, including feature-ready datasets, RAG pipelines, and vector embedding storage.
• Manage Fabric capacity planning, workspace organization, and performance optimization.
• Implement data governance practices, including access controls, lineage tracking, and metadata management, consistent with data classification standards.
• Partner with business-system owners to understand upstream data structures and manage change impacts.
• Collaborate with the Data Scientist to ensure pipeline outputs support analytical and machine-learning use cases.
• Collaborate with Data Analysts to support paginated reporting, dashboards, and self-service BI needs.
• Collaborate with Software Development and DevOps teams to support application development needs.
• Coordinate with third-party consultants as needed to deliver data engineering projects and augment capacity.
• Develop and maintain documentation for pipelines, schemas, and integration logic.
• Troubleshoot and resolve pipeline failures, latency issues, and data-quality incidents.
• Monitor and maintain data-specific infrastructure, including Fabric capacity, orchestration tools, and monitoring and alerting systems.
• Evaluate and recommend data engineering tools, patterns, and best practices.
• Stay current on trends in data engineering, cloud data platforms, and integration techniques.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level