Data Warehouse Engineer
Job no: 525982
Position type: Staff Full Time
Location: UMass Amherst
Division/Equivalent: Univ of Mass Amherst
School/Unit: IT Engineering
Categories: Computer & Information Technology, PSU A
About UMass Amherst
UMass Amherst, the Commonwealth's flagship campus, is a nationally ranked public research university offering a full range of undergraduate, graduate and professional degrees. The University sits on nearly 1,450-acres in the scenic Pioneer Valley of Western Massachusetts and offers a rich cultural environment in a bucolic setting close to major urban centers. In addition, the University is part of the Five Colleges (including Amherst College, Hampshire College, Mount Holyoke College, and Smith College), which adds to the intellectual energy of the region.
Job Summary
The Data Engineer plays a critical role in developing, managing and optimizing the University’s centralized data warehouse, which aggregates data from diverse systems and sources across the entire campus ecosystem. As part of a collaborative team, this individual will be responsible for ensuring the smooth operation and continual enhancement of the data warehouse infrastructure. This position ensures integration with the University’s central analytics platform so that data can be used in real time for interactive dashboards that drive key initiatives for the university. This position requires a blend of technical expertise, problem-solving abilities, and a deep understanding of data systems to ensure seamless data availability for reporting, analysis, and live dashboards that support the university's strategic initiatives.
Essential Functions
- Work with key stakeholders to define the data warehouse's core technical requirements, ensuring that it supports the long-term needs of the university while being flexible for future growth and additional data sources.
- Ensure that the warehouse is scalable, capable of handling future data growth and the integration of new data sources.
- Collaborate with senior engineers to design, build, and maintain data pipelines across a wide variety of programs and current and historical sources. Develop ETL processes. Develop data modeling and database design activities concurrent with the specific needs for stakeholders and projects Collaborate with business analysts, data scientists, and other teams across the university to understand their data needs and translate these into data models, ETL workflows, and reports.
- Support day to day operations for the data warehouse. Monitor and optimize integration performance for data. Perform data quality checks and troubleshooting to ensure data accuracy.
- Create comprehensive documentation detailing the data warehouse architecture, ETL processes, data flows, and technical decisions.
- Stay current with emerging technologies and best practices in data engineering.
- Follow best practices for data governance, ensuring compliance with university policies and data security standards.
- Participate in data warehouse projects, work with the senior developers and business analyst(s) to develop project roadmaps.
- Optimize warehouse performance and provide ongoing troubleshooting and support.
Other Functions
Performs other duties as assigned.
Minimum Qualifications (Knowledge, Skills, Abilities, Education, Experience, Certifications, Licensure)
- Bachelor’s degree in a related field with 5 years work experience supporting technical infrastructure, cloud orchestration or coding in a data driven business environment; a Master’s degree may substitute for 2 year of required experience.
- Strong working knowledge to utilize programming languages and relational databases.
- Strong working knowledge of data warehousing concepts and tools, ETL tools, and documentation for large data sets.
- Strong problem-solving skills and attention to detail.
- Ability to work collaboratively in a team environment and communicate effectively.
- Excellent analytical and organizational skills for discovery, consultation, and implementation of processes and projects.
Preferred Qualifications (Knowledge, Skills, Abilities, Education, Experience, Certifications, Licensure)
- Experience working in a large and/or complex educational environment.
- Experience with SQL and my SQL programming. Solid knowledge of programming languages such as Python, Java, or Scala.
- Experience with cloud data warehouse solutions (e.g. Snowflake and Redshift)
- Experience with data processing frameworks (e.g., Apache Spark, Hadoop).
- Experience with cloud platforms (e.g., AWS, Google Cloud, Azure).
- Knowledge of data visualization tools (e.g., Tableau, Power BI).
- Familiarity with version control systems (e.g., Git).
Physical Demands/Working Conditions
Typical Office Environment Activity.
Work Schedule
Monday to Friday 9:00AM to 5:00PM
Salary Information
Level 27
Special Instructions to Applicants
Along with the application, please submit a resume and cover letter. References will be checked at the finalist stage, please be prepared to provide contact information for three (3) professional references.
UMass Amherst is committed to a policy of equal opportunity without regard to race, color, religion, caste, creed, sex, age, marital status, national origin, disability, political belief or affiliation, pregnancy and pregnancy-related condition(s), veteran status, sexual orientation, gender identity and expression, genetic information, natural and protective hairstyle and any other class of individuals protected from discrimination in employment, admission to and participation in academic programs, activities, and services, and the selection of vendors who provide services or products to the University. To fulfill that policy, UMass Amherst is further committed to a program of affirmative action to eliminate or mitigate artificial barriers and to increase opportunities for the recruitment and advancement of qualified minorities, women, persons with disabilities, and covered veterans. It is the policy of UMass Amherst to comply with the applicable federal and state statutes, rules, and regulations concerning equal opportunity and affirmative action.
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