S'INSCRIRE

Offres d'emploi

Trouvez des postes près de chez vous, sur site, hybrides ou à distance.
  • Emplois similaires à : Lead Data Engineer (T2)
XX
Lead Data Engineer (Data Engineer)Indiana University • Bloomington, Illinois, United States
Postuler Maintenant
XX

Lead Data Engineer (Data Engineer)

Indiana University
  • US
    Bloomington, Illinois, United States
  • US
    Bloomington, Illinois, United States
Postuler Maintenant

À propos

Job Summary
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 Combinations of related education and experience may be considered. Education beyond the minimum required may be substituted for work experience. Work experience beyond the minimum required may be substituted for education.
Education
Bachelor's degree (preferably in computer science, information science, or related field)
Work Experience
5 years data management, engineering, or related experience
Preferred Education / Experience
Experience contributing to communities of practice or cross‑functional innovation teams is a plus.
Skills Required
Proficient written and verbal communication skills
Maintains a high degree of professionalism
Demonstrated 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.
Working Conditions / Demands This role requires the ability to effectively communicate and to operate a computer and other standard office productivity equipment. The position involves sedentary work as well as periods of time moving around an office environment and the campus. The person in this role must be able to perform the essential functions with or without an accommodation.
Work Location This position is eligible for remote work or to work a hybrid schedule (mix between remote and in‑person work), subject to change in the future based on university policy and business needs.
Benefits Overview For full‑time staff employees, Indiana University offers a wide array of benefits including:
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)
Learn more about our benefits by reviewing the IU Benefit Programs Brochure.
Job Classification Career Level: Advanced
FLSA: Exempt
Job Function: Information Technology
Job Family: Data Analysis & Engineering
Click here to learn more about Indiana University's Job Framework.
Posting Disclaimer This posting is scheduled to close at 11:59 pm EST on the advertised Close Date. This posting may be closed at any time at the discretion of the University, but will remain open for a minimum of 5 business days. To guarantee full consideration, please submit your application within 5 business days of the Posted Date.
If you wish to include a cover letter, you may include it with your resume when uploading attachments.
Equal Employment Opportunity 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.
#J-18808-Ljbffr
  • Bloomington, Illinois, United States

Compétences linguistiques

  • English
Avis aux utilisateurs

Cette offre provient d’une plateforme partenaire de TieTalent. Cliquez sur « Postuler maintenant » pour soumettre votre candidature directement sur leur site.