Interested in this Data Engineer role at Illinois State University?
Apply Now →About This Role
- Normal, Illinois, Illinois, United States
- Hybrid
- On Campus
- Remote
- Closing at: Oct 1 2026 - 23:55 CDT
Title: Director of Data Engineering and Data Science
Division Name: Finance and Planning
Department: Decision Support
Job Summary
The Data Engineering & Data Science team within the Office of Decision Support is responsible for scoping, designing, and delivering solutions to business problems using a combination of enterprise data warehouse and business intelligence assets.
The Director of Data Engineering and Data Science is charged with:
- Creating a vision and goals for the Data Engineering and Data Analytics unit in support of the University's strategic plan
- Overseeing the design, implementation, and maintenance of data pipelines, data integration processes, data warehouses, or other data platforms.
- Planning, organizing, staffing, directing, and providing oversight of the work of the unit
- Understanding industry standards, trends and best practices to ensure successful management of opportunities and risks for the reporting and data warehouse environment
- Shaping the business intelligence strategy, data management strategies, and business intelligence architecture
- Helping the University optimize its data assets by understanding and promoting best practices in data management, customer service, data quality, and data security and confidentiality.
Additional Information
There is the potential for 100% remote work in this position, within the State of Illinois. Eligibility is based upon employee performance, appropriate remote working environment, and business needs.
The Data Engineering & Data Science team provides a strong business intelligence environment that helps the University make informed and strategic decisions. This groups manages the Enterprise Data Warehouse and provides data access and training.
https://data.illinoisstate.edu/
University Benefit Highlights:
- Insurance benefits, including health, dental, vision, and life
- Retirement and supplemental retirement planning options
- Tuition waiver benefits available to staff as well as their eligible dependents
- Paid holiday/administrative closures during Thanksgiving and Winter Breaks
- Paid benefit time
For more University Benefit information: https://hr.illinoisstate.edu/benefits/
Information regarding eligibility for participation in the State Universities Retirement System and the State of Illinois Group Insurance program can be reviewed here https://hr.illinoisstate.edu/benefits/insurance/
Salary Rate / Pay Rate
$125,000 - $135,000 annual
Required Qualifications
- Bachelor’s (or higher) Degree
- Minimum of eight (8) years of experience which included the following:
a. Providing successful project management and guidance to others
b. Supervising a technical team
c. Collecting, analyzing, and interpreting business and management needs/requirements
d. Developing test cases, writing use cases, facilitating meetings, creating deliverables, and establishing healthy business relationships
- Minimum of three (3) years experience which included the following:
a. Leading teams of Data Modelers, ETL or Data Warehouse developers, and Data Scientists
b. Leading large-scale data analysis and/or data warehousing projects
c. Presenting data warehousing or data analysis topics to leadership, functional and user audiences.
d. Using data warehousing and data analytics best practices.
- Proven ability to balance theory and practical business reality to produce results
- Commitment to customer-driven development, service excellence and user satisfaction.
- Ability to work collaboratively with campus colleagues, vendors and consultants.
- Leadership skills that engender trust and mutual respect.
- Excellent written and oral communication skills.
Preferred Qualifications
Minimum of 10 years’ experience working at a higher education institution
Work Hours
Core work hours: Monday - Friday; 8:00 a.m. - 4:30 p.m.
Functional Expectations
Must be able to complete the following with or without a reasonable accommodation:
- Remain at a workstation for extended periods.
- Distinguish colors on a monitor.
- Effectively communicate on a daily basis.
Proposed Starting Date
October 2026
Required Applicant Documents
Resume
Cover Letter
Reference List
Transcripts - See Special Instructions to Applicants for additional options
Please Note: These documents are required to be submitted online in order to complete the application process. Please have these documents ready prior to clicking on "Apply"
Optional Applicant Documents
Certification of Retirement Annuity
Please Note: These documents may be submitted online in order to complete the application process. Please have these documents ready prior to clicking on "Apply"
Special Instructions for Applicants
Sponsorship: Applicants for this position must be currently legally authorized to work for Illinois State University in the United States. Illinois State University will not sponsor or take over the sponsorship of an employment visa for this opportunity. Illinois State University is not a qualifying employer for the STEM OPT benefit: only the 12-month OPT may be used to work at Illinois State University.
Please fully complete the entire application including, but not limited to, the education and work history portions. Be specific on your work history, including employment dates (if part-time you must list the number of work hours) and duties for all positions held. Applicable part-time work experience will be considered toward qualifying for this position; however, it will be converted to a full-time equivalency to determine combined length of experience. Please do not put "see resume" in the duties and responsibilities section of the work history. This will be considered an incomplete application and incomplete applications will not be considered.
College or university transcripts (may be unofficial) must be submitted prior to the application deadline to receive full consideration. Transcripts can either be uploaded with your application or submitted via the options listed below.
To be eligible for Veteran's Preference points on the exam, appropriate military service documentation such as a DD-214 must be submitted prior to the application deadline.
Transcripts and/or military service documentation may be emailed, faxed, or mailed to Human Resources by the application deadline:
Fax: 309.438.0011, Attn: Colette Homan
Address: Illinois State University
Human Resources
Campus Box 1300
Normal, IL 61790-1300
The Civil Service examination for this classification is based on your application materials and responses to the supplemental questions. No participation other than submission of applicant materials is required from applicants that qualify to take the exam. If you meet the minimum required qualifications for this position, you will receive a score calculated based on your education and experience, and your name will be placed on the active employment register by exam score. After the application deadline, the names within the top three scores will be referred to the department for interview. The active register for this classification will be voided when the position is filled.
Illinois State University is authorized to do business within the State of Illinois. All work under this appointment is required to be performed from within the State of Illinois. If hired, out-of-state candidates must establish Illinois residency within 180 calendar days from the start date for this position. Illinois residency requires proof of a valid Illinois driver’s license or a valid State of Illinois ID card. Failure to produce the required documentation within 180 calendar days will result in immediate termination of employment.
Contact Information for Applicants
Colette Homan
Human Resources
309-438-8848
Important Information for Applicants
This position is subject to a criminal background investigation and if applicable, an employment history review, based on University Policy 3.1.30 and any offer of employment is contingent upon you passing a satisfactory criminal background investigation and/or an employment history review. You may not begin work until the criminal background investigation results have been received and cleared by Human Resources.
Illinois State University is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
If you are an individual with a disability and need a reasonable accommodation under the Americans with Disabilities Act (ADA) or other state or federal law you may request an accommodation by contacting the Office of Equal Opportunity and Access at (309) 438-3383. The Office of Equal Opportunity and Access will hold any confidential information you provide in confidence.
If you are having difficulty accessing the system, please call Human Resources at (309) 438-8311.
Salary Context
This $125K-$135K range is below the median for Data Engineer roles in our dataset (median: $150K across 25 roles with salary data).
Role Details
About This Role
Data Engineers build the pipelines that feed AI models. They design ETL workflows, manage data lakes, and ensure training and inference data is clean, timely, and accessible. Without good data engineering, AI projects fail. It's that simple.
The AI era has expanded the data engineer's scope far beyond batch ETL jobs. You're building real-time embedding pipelines for RAG systems, managing vector databases, ensuring training data quality at scale, and building the infrastructure that lets ML teams iterate on data as fast as they iterate on models. Data quality is the biggest predictor of model quality, and you're the person responsible for it.
Across the 8,943 AI roles we're tracking, Data Engineer positions make up 1% of the market. At Illinois State University, this role fits into their broader AI and engineering organization.
Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.
What the Work Looks Like
A typical week includes: debugging a data pipeline that's producing stale embeddings for the RAG system, optimizing a Spark job that processes training data, building a data quality monitoring dashboard, meeting with the ML team to understand their next data requirements, and writing dbt models that transform raw event data into ML-ready features. The work is deeply technical and high-impact.
Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.
Skills in Demand for This Role
SQL, Python, and distributed systems (Spark, Airflow, dbt) are core. Cloud data platforms (Snowflake, BigQuery, Redshift) are increasingly standard. Many AI-focused roles also want familiarity with vector databases and embedding pipelines. Understanding data modeling, pipeline orchestration, and data quality frameworks covers the essentials.
AI-specific data engineering skills include: building feature stores, managing training data versioning, implementing data lineage tracking, and building real-time embedding pipelines. Experience with streaming systems (Kafka, Flink) is valuable for real-time AI applications. Understanding ML data requirements (balanced datasets, data augmentation, evaluation set construction) makes you much more effective working with ML teams.
Strong postings specify the data stack, mention ML pipeline work, and describe the scale of data you'll be working with. Look for companies that understand the connection between data quality and model quality. Avoid roles that conflate data engineering with data analysis.
Compensation Benchmarks
Data Engineer roles pay a median of $177,825 based on 160 positions with disclosed compensation. Director-level AI roles across all categories have a median of $272,250. This role's midpoint ($130K) sits 27% below the category median. Disclosed range: $125K to $135K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.
Illinois State University AI Hiring
Illinois State University has 1 open AI role right now. They're hiring across Data Engineer. Based in Normal, IL, US. Compensation range: $135K - $135K.
Location Context
Across all AI roles, 6% (521 positions) offer remote work, while 8,351 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,416 roles, $263,811 median); Los Angeles (1,340 roles, $210,000 median).
Career Path
Common paths into Data Engineer roles include Backend Engineer, Database Administrator, Analytics Engineer.
From here, career progression typically leads toward Senior Data Engineer, ML Engineer, Data Platform Lead.
Master SQL and Python first. Then learn a distributed processing framework (Spark or its modern alternatives) and a pipeline orchestrator (Airflow, Dagster, Prefect). Build a portfolio project that demonstrates end-to-end pipeline construction: ingest, transform, validate, serve. If you want to specialize in AI data engineering, add vector databases and embedding pipelines to your skill set.
What to Expect in Interviews
Expect SQL deep-dives (query optimization, partitioning strategies, data modeling), Python coding focused on data pipeline patterns, and system design questions about building scalable ETL workflows. Companies with ML teams will ask about feature stores, embedding pipelines, and training data management. Be ready to discuss data quality monitoring, pipeline orchestration, and how you'd handle schema evolution in a production data lake.
When evaluating opportunities: Strong postings specify the data stack, mention ML pipeline work, and describe the scale of data you'll be working with. Look for companies that understand the connection between data quality and model quality. Avoid roles that conflate data engineering with data analysis.
AI Hiring Overview
The AI job market has 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.
The AI Job Market Today
The AI job market spans 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (175) are outnumbered by mid-level (4,132) and senior (3,268) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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