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NEXTMOVEFDE careers · United States

Data Engineer II

No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.

About University of Texas at Austin

Texas' flagship public research university running 18 schools, Dell Medical School, TACC, ARL:UT, and a fast-scaling semiconductor/AI research enterprise in Austin.

Bootstrapped · 5000+ people

Job description

The full responsibilities and requirements are on the employer’s site.

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Internal deployment & tooling · Evidence for this classification:

Job Posting Title: Data Engineer II ---- Hiring Department: Dell Medical School ---- Position Open To: All Applicants ---- Weekly Scheduled Hours: 40 ---- FLSA Status: Exempt from FLSA ---- Earliest Start Date: Immediately ---- Position Duration: Expected to Continue ---- Location: AUSTIN, TX ---- Job Details: General Notes Data Engineer II is an experienced data professional responsible for designing, building, and maintaining robust data pipelines and infrastructure that enable the collection, storage, and processing of large datasets. This role expands upon the Data Engineer I position by handling more complex data projects and working with greater independence. A Data Engineer II ensures data is accurate, secure, and compliant with data governance standards. A Data Engineer II collaborates with cross-functional teams (e.g., business stakeholders, IT, and subject-matter
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Job Posting Title: Data Engineer II ---- Hiring Department: Dell Medical School ---- Position Open To: All Applicants ---- Weekly Scheduled Hours: 40 ---- FLSA Status: Exempt from FLSA ---- Earliest Start Date: Immediately ---- Position Duration: Expected to Continue ---- Location: AUSTIN, TX ---- Job Details: General Notes Data Engineer II is an experienced data professional responsible for designing, building, and maintaining robust data pipelines and infrastructure that enable the collection, storage, and processing of large datasets. This role expands upon the Data Engineer I position by handling more complex data projects and working with greater independence. A Data Engineer II ensures data is accurate, secure, and compliant with data governance standards. A Data Engineer II collaborates with cross-functional teams (e.g., business stakeholders, IT, and subject-matter experts) to deliver solutions that meet business and research needs. Responsibilities Maintains and optimizes data pipeline architecture by designing, building, and managing ETL processes that extract, transform, and load data from diverse sources. Assembles large, complex data sets to meet both functional and non-functional requirements, and develops scalable architectures for structured and unstructured data. Integrates and consolidates data from multiple systems—such as disparate databases and [... source excerpt omitted ...] s across departments—including executives, product managers, researchers, and designers—to address data infrastructure needs and resolve technical issues. Translates non-technical requirements into effective data solutions and advises on best practices for data architecture. Manages and executes data projects from planning through deployment. Applies light project management techniques to coordinate tasks, communicates with team members, and ensures timely delivery. Exercises independent judgment to overcome obstacles and align project outcomes with organizational goals. MARGINAL OR PERIODIC FUNCTIONS: Adheres to internal controls and reporting structure. Performs related duties [... source excerpt omitted ...] zes tasks and manages time effectively. Breaks down complex projects into manageable steps. Tracks progress and adjusts plans as needed. Meets deadlines consistently. Required Qualifications Requires a Bachelor's Degree in Computer Science, Information Systems, Data Science, or a related field (required). An equivalent combination of relevant education and experience may be considered in lieu of a four-year degree with at least 4 year(s) of experience in data engineering or a closely related field. This experience should include designing data architectures, developing data pipelines, and implementing data quality/performance monitoring. Proven track record in database development

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