Senior IT Data Engineer
Listed on 2026-07-23
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IT/Tech
Data Analyst, Data Engineering, AI Engineer (Applied/Software), Machine Learning/ ML Engineer
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Best People + Right Culture. These are the driving forces behind JE Dunn’s success.
By hiring inspired people, giving them interesting and challenging work, enabling them with innovative tools, and letting them share in the company’s rewards, we’ve found a sustainable way to grow in our industry for the last 100+ years.
Our diverse teams around the country strive to enrich lives through inspired people and places everyday, and we need inspired people like you to join us in our pursuit of building perfection.
Role SummaryThe 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.
- Core
- 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
- Additional Core
SENIOR DATA ENGINEER
In addition, this position will be responsible for the following:
- 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…
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