Data Analytics Engineer, College of Natural Sciences

utaustin; Utah; On-site; USD 90,000 - 140,000; Full time

Job summary

University of Texas at Austin – College of Natural Sciences is seeking a Data Analytics Engineer to design, develop and support integrated data solutions across academic, research and administrative functions. You will work closely with faculty, researchers and IT peers to deliver robust data structures within the UT Data Hub framework.

In this role you will translate institutional needs into scalable pipelines, create analytics and dashboards, and ensure data governance and privacy compliance

Qualifications

• Bachelor's degree or equivalent experience in CS/IS/Data Science.
• Strong SQL skills to query large databases and validate data.
• Knowledge of databases, data flows, and data manipulation.
• Ability to synthesize complex information from multiple sources.
• Excellent communication with diverse stakeholders.

Responsibilities

• Design, develop, and support integrated data solutions.
• Collaborate with academic units and IT partners to gather requirements.
• Translate needs into scalable data structures and pipelines.
• Maintain governance, privacy, and compliance across datasets.
• Create descriptive, predictive, and prescriptive analytics and reports.
• Develop dashboards and tools for university decision-making.

Skills

SQL

Data analysis

Communication

Organizational skills

Problem-solving

Education

Bachelor's degree or equivalent experience

Tools

PostgreSQL

Job description

Job Posting Title

Data Analytics Engineer, College of Natural Sciences

Hiring Department

College of Natural Sciences

Position Open To

All Applicants

Weekly Scheduled Hours

40

FLSA Status

Exempt from FLSA

Earliest Start Date

Oct 01, 2026

Position Duration

Expected to Continue

Location

UT MAIN CAMPUS

Job Details

General Notes

This position is not eligible for employer-sponsored work authorization. Applicants must be authorized to work in the United States for any employer now and in the future without sponsorship.

The College of Natural Sciences at UT Austin, strives to foster a work environment that enables all employees to contribute at the highest possible level to support the mission of the University. What starts here really does change the world. For more information about the College of Natural Sciences, please visit https://cns.utexas.edu . The university also offers an impressive benefits package. For more information, see Prospective Employee Benefits.

Purpose

The Data Analytics Engineer designs, develops, and supports integrated data solutions that enable informed decision-making across academic, research, and administrative functions of the university. This role plays a key part in managing and integrating data across multiple environments, including combining local data with central campus datasets within the UT Data Hub framework.

Working closely with academic units, central offices, researchers, and IT partners, this position translates institutional needs into robust, efficient, and scalable data structures while operating within university data governance, privacy, and compliance requirements.

Responsibilities

Data Analytics and Data Engineering

• Develops, codes, validates, and implements relational databases and integrated data structures that support analytics.
• Collaborates with functional partners to collect business requirements and develop and refine business logic.
• Collaborates with technical partners to locate, clean, and orchestrate source data.
• Crafts code for the translation and transformation of functional business logic into a high-scale database environment that can readily support the production of descriptive, predictive, and prescriptive analytics and consumable reports, dashboards, and other tools to support University decision-making.
• Understands how to best design database structures for meaningful data visualizations and interactive tools.
• Engages in best practices in data analytics and data engineering - including robust validation processes, testing/deployment procedures, algorithms for data mining, version control and code integration, thorough documentation, and automation and streamlining of data processing pipelines.
• Applies creativity and flexibility to finding solutions for new institutional data challenges.
• Assists with special projects and ad hoc data requests as needed.

Collaboration, Communication, & Institutional Knowledge

• Works both independently and collaboratively with cross-functional teams to develop exceptional data products to meet university needs.
• Participates in data project lifecycle - from conception, requirements gathering and design, documentation, development and testing through deployment.
• Engages and communicates with partners and stakeholders to manage requests, expectations, and deliverables.
• Effectively communicates project status, progress, risks, and issues to drive project to completion.
• Develops an in-depth knowledge of university data processes and technologies.
• Handles confidential information with tact and discretion.

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, Data Science, or a related field, or equivalent professional experience.
• Strong technical expertise in using SQL to query large databases, manipulate and validate data, implement business logic, and analyze data.
• Excellent knowledge of databases, data flows, and data manipulation in both operational and analytical contexts.
• Proven ability to synthesize complex and/or ambiguous information from multiple sources using a variety of tools and techniques to transform that information into consumable insights.
• Ability to communicate with a wide range of stakeholders and collaborate effectively in a higher-education or enterprise setting.
• Proven prioritization and organizational skills with the ability to handle multiple projects simultaneously.
• Excellent written and verbal communication skills, critical thinking and creative problem-solving, and attention to detail.
• Demonstrated ability to maintain a high level of professionalism.
• Relevant education and experience may be substituted as appropriate.

Preferred Qualifications

• Experience working in a higher education or research environment.
• Familiarity with institutional data domains (e.g., student, enrollment, research, finance, HR).
• Experience working with cloud data platforms or analytics services and PostgreSQL env