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Research Data Engineer I

Rochester Open
Rochester Mid-level Data Engineering

At a glance

Mid-level Data Engineering role at Rochester. Rochester · no salary stated · we estimate $112,500–$160,000 across the United States.

Estimated pay

Rochester has not published a salary for this role. The figure below is our estimate, not theirs.

$112,500 – $160,000
What the middle half of mid-level data engineering roles in the United States paid, among postings that did state a salary.
Worked out from 439 postings that stated pay, median $135,000. Last updated Nov 6, 2026.
RoleData Engineering
SeniorityMid-level
LocationRochester
PostedJul 11, 2026
Role brief

dataroles summary, based on the employer's posting.

What you'll do

  • Maintain and update ETL pipelines and data architecture as research datasets grow and arrive from varied sources
  • Help turn business and technical needs into software, while tracking assignments, deadlines and user expectations
  • Build research-specific workflows for collecting, managing, reporting and analyzing data
  • Follow development and testing practices, review code, check deliverables and document the systems you support

What you bring

  • A bachelor's degree in data science, computer science or a related listed discipline, plus at least one year of relevant experience
  • Programming experience with SQL or an equivalent combination of education and experience
  • Experience in technology-intensive settings and the ability to apply software development practices

Who this fits

This mid-level role suits someone who can support scientific data workflows under moderate guidance and coordinate with a team and research users. The work is scheduled per diem, on the day shift, with an 8 AM to 5 PM schedule in Rochester, New York.

From the employer

As a community, the University of Rochester is defined by a deep commitment to Meliora - Ever Better. Embedded in that ideal are the values we share: equity, leadership, integrity, openness, respect, and accountability. Together, we will set the highest standards for how we treat each other to ensure our community is welcoming to all and is a place where all can thrive.

Job Location (Full Address):

220 Hutchison Rd, Rochester, New York, United States of America, 14620

Opening:

Worker Subtype:

Regular

Time Type:

Time as Reported / Per Diem

Scheduled Weekly Hours:

As Scheduled

Department:

400295 Cancer Center Admin M&D

Work Shift:

UR - Day (United States of America)

Range:

UR URG 109 H

Compensation Range:

$27.16 - $38.03

The referenced pay range represents the minimum and maximum compensation for this job. Individual annual salaries/hourly rates will be set within the job's compensation range, and will be determined by considering factors including, but not limited to, market data, education, experience, qualifications, expertise of the individual, and internal equity considerations.

Responsibilities:

With moderate supervision and guidance, supports the implementation and maintenance of analytical and data science-based software and data pipelines, enabling scientific workflows. Provides focused support in enhancing the data collection frameworks that integrate structured and unstructured data from multiple sources and systems to enable the used of data in specific research study teams. Maintains and supports the development of infrastructure systems (e.g., data warehouses, data lakes, etc.), including data access APIs. Receives guidance from and acts in support of a team aimed at providing robust, scalable software solutions to the research enterprise.

JOB DUTIES AND RESPONSIBILITIES:

  • Maintains and modifies Extract Transform and Load (ETL) data pipelines and overall data architecture to accommodate a growing amount of data from a variety of large research data sources.
  • Works with team members to support the conversion of business and technical requirements into professional software solutions. Ensures timely completion of tasks while managing multiple assignments, project timelines and business user expectations.
  • Supports the implementation of custom, research project-specific data workflow solutions for data collection, management, reporting and analytics. Contributes to the scientific research.
  • Adheres to defined application development life-cycle practices, including but not limited to, requirements gathering, writing test plans, source code management, peer code review and quality assurance through unit/system/user acceptance testing.
  • Participates in specification, implementation and execution of testing procedures to ensure quality of deliverables, system and data workflow reliability.
  • Produces and maintains comprehensive technical documentation for all systems under the Engineer's responsibilities.
  • Keeps abreast of current application developments through continuing education, professional reading, online forums, conferences, workshops and professional groups.
  • Other duties as assigned.

QUALIFICATIONS:

  • Bachelor's degree in Data Science, Biomedical Science, Computer Science, Mathematics, Statistics or similar discipline required.
  • 1 year of relevant experience required including experience in technology-intensive environments and programming experience in SQL or equivalent combination of education and experience.
  • Programming experience, ideally in Java and Python and/or R; Experience with laboratory data management systems (e.g. biospecimen software, electronic laboratory notebooks, LabKey Server, REDCap);
  • Experience with Linux environments, Docker, and cloud technologies (e.g. AWS, Microsoft Azure, Google Cloud Platform).
  • Familiarity with data analytics and statistical methods;
  • Expertise of software engineering best practices such as version control and software release management;
  • Strong analytical and problem-solving skills;
  • Strong organizational skills;
  • Ability to work with others in a matrix management environment;
  • Excellent communication skills for describing progress and challenges to stakeholders;
  • Attention to detail, patience and a positive, customer-centric attitude;
  • Strong technical presentation skills;
  • Demonstrated ability to develop proficiency with unfamiliar toolsets.
  • Familiarity with genomics, metagenomics, flow cytometry or imaging files, metadata, and data standards preferred.

Schedule

8 AM-5 PM

The University of Rochester is committed to fostering, cultivating, and preserving a culture of equity, diversity, and inclusion to advance the University’s mission to Learn, Discover, Heal, Create – and Make the World Ever Better. In support of our values and those of our society, the University is committed to not discriminating on the basis of age, color, disability, ethnicity, gender identity or expression, genetic information, marital status, military/veteran status, national origin, race, religion/creed, sex, sexual orientation, citizenship status, or any other status protected by law. This commitment extends to the administration of our policies, admissions, employment, access, and recruitment of candidates from underrepresented populations, veterans, and persons with disabilities consistent with these values and government contractor Affirmative Action obligations.

The University of Rochester is committed to fostering, cultivating, and preserving an inclusive and welcoming culture to advance the University’s Mission to Learn, Discover, Heal, Create – and Make the World Ever Better. In support of our values and those of our society, the University is committed to not discriminating on the basis of age, color, disability, ethnicity, gender identity or expression, genetic information, marital status, military/veteran status, national origin, race, religion, creed, sex, sexual orientation, citizenship status, or any other characteristic protected by federal, state, or local law (Protected Characteristics). This commitment extends to non-discrimination in the administration of our policies, admissions, employment, access, and recruitment of candidates, for all persons consistent with our values and based on applicable law.

Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Data Engineering

Find me work

By the team behind dataroles.

Find me work
Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind dataroles.