Data Engineer

Baker Group is seeking a Data Engineer to design, build, and maintain Microsoft Fabric data pipelines and infrastructure, enabling the organization’s data platform to function as a single source of truth. This role will own end-to-end ingestion, transformation, orchestration, governance, and preparation of datasets for reporting and AI/ML use cases.

Key Responsibilities

• Design, build, and maintain ETL/ELT pipelines to ingest data from enterprise systems into Microsoft Fabric.
• Architect and maintain the Fabric medallion Lakehouse structure, including bronze, silver, and gold layers, as the single source of truth for Baker Group.
• Implement best practices for the data infrastructure and environment, including Development/Test/Production environments and Git-based version control.
• Own pipeline orchestration, scheduling, and monitoring to support 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 all pipelines.
• Design and manage data models, schemas, and semantic layers that enable Data Analyst reporting and Data Scientist modeling.
• Define and maintain data ontologies and canonical business definitions to keep consistent meaning across systems and data consumers (for example, definitions of “project,” “employee,” or “cost code”).
• Prepare and structure data for AI and machine learning, including feature-ready datasets, retrieval-augmented generation (RAG) pipelines, and vector embedding storage.
• Manage Fabric capacity planning, workspace organization, and performance optimization.
• Implement data governance practices such as access controls, lineage tracking, and metadata management aligned with Baker Group data classification standards.
• Partner with business system owners (ERP, HRIS, MRP, etc.) to understand upstream structures and manage change impacts.
• Collaborate with Data Scientists to ensure pipeline outputs support analytical and machine learning use cases.
• Collaborate with Data Analysts to ensure data products support paginated reporting, dashboards, and self-service BI needs.
• Collaborate with Software Development and DevOps teams to ensure data products support application development needs.
• Coordinate with third-party consultants when needed to deliver data engineering projects and augment capacity for high-demand business needs.
• 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, pipeline orchestration tools, and monitoring/alerting systems.
• Evaluate and recommend new data engineering tools, patterns, and best practices.
• Stay current with emerging trends in data engineering, cloud data platforms, and integration techniques.

Required Qualifications

• 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 schema.
• Understanding of data governance, data quality, and metadata management practices.

Preferred Qualifications

• Experience preparing data for AI/ML consumption (for example, vector embeddings and RAG architectures) is a plus.
• Business acumen and understanding of construction or related industries is a plus.

Technologies

• Microsoft Fabric
• ETL, ELT
• Azure Data Factory
• Git
• SQL
• Python, PySpark
• T-SQL
• Medallion architecture
• Dimensional modeling, star schema
• Retrieval-augmented generation (RAG)
• Vector embedding storage

Minimum Education and Experience Required

• Bachelor’s degree
• 3+ years of experience (data engineering, ETL/ELT development, or related work)

Certifications (Optional)

• No specific requirements; relevant certifications such as Microsoft Certified: Fabric Data Engineer Associate, Azure Data Engineer Associate, or similar cloud platform certifications are a plus.

Competencies and Work Style

• Strong analytical and troubleshooting skills to diagnose and resolve complex pipeline and data quality issues.
• Excellent time and project management skills to prioritize across multiple pipeline and infrastructure projects.
• Strong communication skills, including translating technical data structures for non-technical stakeholders.
• Team-oriented collaboration with Data Scientists, Data Analysts, and business system owners.
• Ability to focus on complex technical problems and work independently with minimal supervision.
• Meticulous attention to detail and a commitment to producing reliable, well-documented data infrastructure.
• Ability to work in a fast-paced environment and adapt to changing business priorities.

Location and Environment

Location: Ankeny, IA (onsite)

• Prolonged periods of sitting at a desk and working on a computer.
• Must be able to lift 10 pounds occasionally.
• May have occasional visits to a job site requiring periods of standing, walking, and/or climbing stairs.

Tools

Use a computer for 8 hours a day.