Lead Data Engineer (Data Engineer)

Indiana University; Bloomington (IN); Hybrid; USD 80,000 - 100,000; Full time

Benefits offered by this job

Comprehensive medical and dental insurance

Tuition subsidy for employees

Generous paid time off

Job summary

Indiana University is seeking an advanced Data Manager for the Kelley School of Business in Bloomington, Indiana. The role includes advanced data management tasks, developing custom systems, and mentoring junior peers. The ideal candidate has a Bachelor's degree in Computer Science and at least 5 years of relevant experience.

Preferred candidates will have familiarity with machine learning models and experience with RESTful APIs. The position offers a hybrid work schedule and comprehensive benefits, including medical insurance and a tuition subsidy for employees.

Qualifications

• 5 years of experience in data management or engineering.
• Ability to process data and engineer features.
• Demonstrated flexibility in a dynamic environment.

Responsibilities

• Perform complex data modeling and migration tasks.
• Design and implement custom data systems.
• Provide advanced troubleshooting for data issues.

Skills

Proficient communication skills

High commitment to quality

Time management

Familiar with machine learning models

Experience with RESTful APIs

Education

Bachelor's degree in Computer Science or related field

Tools

Azure

Docker

Python

Job description

KELLEY SCHOOL OF BUSINESS (BL-BUS-IUBLA)

The Kelley School of Business at Indiana University (IU) is a comprehensive provider of top-tier business education with a full portfolio of undergraduate, graduate, doctoral, and executive programs on campuses in Bloomington and Indianapolis, and online worldwide. The Kelley School has been creating career momentum for 100 years, going from 70 students in 1920 to an enrollment of more than 15,000 students today. Our innovative curriculum is built on personal development, teamwork, and experiential learning with an emphasis on global and social responsibility. Our success is reflected in our reputation among academic peers, our career placement statistics, and the accomplishments of more than 137,000 living alumni around the globe.

Responsibilities

• Performs advanced data management tasks, including complex data modeling, conversion, de-duplication, migration, and identification and repair of data quality issues.
• Designs, develops, and implements complex custom data systems and advanced reconciliation tools, processes, rules, solutions etc. to validate data, match/merge, and upload batch lists.
• Creates and tunes highly complex stored procedures and queries for advanced data management and extraction.
• May contribute to committees and communities of practice to share and improve data engineering practices across the university; provides a high level of consultation and mentoring to other groups and staff on the use of data engineering tools and software.
• Makes recommendations to improve, as well as implements, documentation and security protocols and procedures for data engineering projects and/or activities; fixes complex problems and resolves issues accordingly.
• Provides advanced troubleshooting and problem analysis/resolution for data related issues; acts as a point of escalation for junior team members; performs advanced scripting and modifications of application and products for corrective action.
• Performs advanced-level research and stays up-to-date with data engineering best practices and approaches; stays abreast of latest security threats and risks to proactively address potential exposures.
• May serve as project lead; often provides guidance to junior peers.

Qualifications

Education

• Bachelor's degree (preferably in computer science, information science, or related field).

Work Experience

• 5 years data management, engineering, or related experience.

Skills

• Proficient communication skills.
• Maintains a high degree of professionalism.
• Demonstrates time management and priority setting skills.
• Demonstrates a high commitment to quality.
• Possesses flexibility to work in a fast paced, dynamic environment.
• Seeks to acquire knowledge in area of specialty.
• Highly thorough and dependable.
• Demonstrates a high level of accuracy, even under pressure.
• Possesses a high degree of initiative.
• Ability to influence internal and/or external constituents.

Preferred

• Familiarity with conventional machine learning models and processes, including classification, clustering, and retrieval.
• Demonstrated experience integrating AI/LLM models (e.g., LLaMA via Ollama, OpenAI, Claude, or Amazon Bedrock) into enterprise platforms and services.
• Ability to process data and engineer features for downstream model integrations.
• Experience with prompt engineering, inference pipelines, and APIs for deploying AI agents at scale.
• Experience with fine-tuning and/or supervising model adaptation to domain-specific data and use cases.
• Experience with agentic frameworks such as Langgraph, Diffy, or related technologies.
• Knowledge on tracking data and model lineages including the ability to ensure security and compliance of the deployed models to comply with appropriate governance, to manage role-based access to services, and to apply data masking where necessary.
• Ensuring security and compliance of the deployed models to comply with appropriate governance, managing role-based access to services, and applying data masking where necessary.
• Experience building or consuming data virtualization layers to abstract complex enterprise data systems for AI consumption.
• Strong understanding of modern data architectures (data lakes, lakehouses, vector stores) and API-first approaches to data access and transformation.
• Familiarity with vector databases (e.g., Marqo, Milvus, Pinecone) and embedding models for semantic search and retrieval-augmented generation (RAG).
• Proficiency in building and maintaining RESTful APIs that interface with internal systems, enabling AI-enhanced features in existing applications.
• Experience with cloud services (Azure, AWS), containerized deployments (e.g., Docker), and CI/CD workflows.
• Comfort working with both in-house developed tools and open-source AI/ML infrastructure.
• Openness to hybrid .NET and Python ecosystems to support the evolving needs of our AI integration efforts.
• Passion for supporting digital transformation through AI education and enablement across diverse stakeholder groups, including non-technical faculty and staff.
• Demonstrated ability to explain complex technical concepts to a wide range of audiences, and a commitment to building reusable resources, guides, and documentation.
• Strong curiosity, experimental mindset, and a desire to shape the future of AI in higher education.
• Interest in bridging research, teaching, and operations with intelligent systems and modern data practices.
• Ability to work iteratively in a fast-moving environment where priorities evolve as innovation unfolds.

Benefits

• Comprehensive medical and dental insurance.
• Health savings account with generous IU contributions.
• Healthcare and dependent care flexible spending accounts.
• Basic group life insurance paid by IU.
• Voluntary supplemental life, long-term disability, critical illness, and supplemental accidental death & dismemberment insurance.
• Base retirement plan with generous IU contributions, subject to vesting.
• Voluntary supplemental retirement plan options.
• Tuition subsidy for employees and family members taking IU courses.
• 10 paid holidays plus a paid winter break each year.
• Generous paid time off plans.
• Paid leave for new parents and IU-sponsored volunteer events.
• Employee assistance program (EAP).

Career Level: Advanced

FLSA: Exempt

Job Function: Information Technology

Job Family: Data Analysis & Engineering

Indiana University is an equal opportunity employer and provider of ADA services and prohibits discrimination in hiring. See Indiana University Notice of Non-Discrimination here which includes contact information.

This position is on a 3-year limited term appointment.

This position is eligible for remote work or to work a hybrid schedule subject to change in the future based on university policy and business needs.