Senior IT Data Engineer

J.E. Dunn Construction Group Inc P•Kansas City, MO

13d•Onsite

About The Position

The Senior Data Engineer designs, implements, and evolves enterprise data and machine learning capabilities using Microsoft Fabric and related modern data platforms. This role emphasizes enabling predictive and prescriptive analytics by building scalable data foundations, partnering with business stakeholders to identify high-value opportunities, and applying a deep understanding of machine learning, data science, and statistical concepts to real business problems. The position operates as a forward-looking technical leader who is comfortable working with rapidly changing technologies—including Fabric, data agents, Rayfin, and large language models—and exploring new ways to create business value from data. All activities will be performed in support of the strategy, vision and values of JE Dunn. Autonomy & Decision-Making: Makes decisions on non-routine matters, provides recommendations to supervisor, and refers all exceptions to supervisor. Career Path: Data Engineering Manager

Requirements

Ability to perform work accurately and completely, and in a timely manner
Communication skills, verbal and written
Time management skills
Ability to prioritize multiple projects
Ability to drive change through innovation & process improvement
Ability to communicate to executive audiences and deliver results through influence
Deep understanding of machine learning, data science, and statistical concepts, including how to apply them to business problems and value creation
Ability to work with business stakeholders to understand available data, identify opportunities, and define high-value predictive and prescriptive analytics use cases
Comfort working with cutting-edge and rapidly changing technologies, including Microsoft Fabric, data agents, Rayfin, and large language models
Ability to think creatively about how emerging technologies can be leveraged in new ways to improve decision-making and business outcomes
Proficiency in SQL – Intermediate
Proficiency in Python – Intermediate
Proficiency in Spark – Intermediate
Experience implementing data architectures and governed analytical data models in modern data platforms
Knowledge of data governance and security best practices
Bachelor’s degree in Computer Science, Data Engineering or related field (Required)
In lieu of the above requirements, equivalent relevant experience will be considered.
5+ years of experience in data analytics or data engineering (Required)

Nice To Haves

Experience developing and consuming REST APIs for data integration (Preferred)
Familiarity with Power BI and Microsoft Fabric (Preferred)
Experience with Microsoft Purview or similar data catalog and governance tools (Preferred)
Experience supporting or operationalizing machine learning models for predictive or prescriptive analytics (Preferred)

Responsibilities

Design and implement scalable data and analytics architectures in Microsoft Fabric that support predictive and prescriptive use cases
Partner with business stakeholders to understand operational challenges, available data, and opportunities to create measurable business value through analytics and machine learning
Apply a strong understanding of machine learning, data science, and statistical concepts to support model development, experimentation, and deployment
Support the development of predictive and prescriptive analytics solutions by preparing reliable, well-governed datasets for training, inference, and decision support
Evaluate emerging technologies such as Fabric, data agents, Rayfin, and large language models, and recommend practical ways to leverage them in new and innovative ways
Design data models and transformation processes that improve data quality, consistency, and usability for advanced analytics
Participate in architectural reviews to ensure new systems align with the organization's data, analytics, and AI strategy
Implement governance, lineage, metadata, and security practices that enable trusted self-service analytics and responsible AI usage
Monitor and improve the performance, reliability, and quality of data and ML workflows, including alerting for data drift and model performance issues
Document analytics and ML data dependencies, solution designs, and technical standards to support maintainability and scale
Collaborate across departments to identify data synergies, prioritize high-impact use cases, and communicate changes to stakeholders
Optimize data processes and platform capabilities to improve the speed, effectiveness, and cost-efficiency of analytics and machine learning solutions
Supports the definition of enterprise patterns and standards for advanced analytics, machine learning, and AI-enabled data products
Provides subject matter expertise for evolving or experimental initiatives involving predictive analytics, prescriptive analytics, and emerging technologies
Mentors junior team members on data science concepts, analytical thinking, and modern data platform best practices
Leads small to medium sized initiatives as a technical subject matter expert in advanced analytics and data architecture
Provides authoritative feedback on how upstream systems, business processes, and data structures can better support analytical and ML outcomes
Collaborates with key stakeholders and IT leadership to identify and prioritize data investments with clear business value
Contributes to the data and AI strategy roadmap and supports complex, high-impact initiatives that leverage modern and rapidly evolving technologies