Lead Data Engineer

5 days ago

Princeton, United States Princeton University Full time

Overview

The Accelerator seeks a head of data to work with team members to lead the design, implementation and development of the Accelerator's data and reporting strategy. Alongside this the position will help us improve our existing data-intensive applications and processes. As part of a small cross-functional team, this individual will participate in product design and iterative development to support the mission of powering policy-relevant research by building shared infrastructure.

As a fully competent professional in all aspects of the subject matter, this individual either
- Normally plans and conducts work requiring judgment in the independent evaluation, selection, and substantial adaptation and modification of standard techniques, procedures, and criteria and devises new approaches to problems encountered. This requires the candidate to have sufficient experience to assure competence as a fully established professional who has completed projects. This staff member performs independently, carrying out assignments with instructions about the general results expected, receiving technical guidance only on unusual problems, and getting supervisory approval on proposed plans for projects before beginning them or
- Applies extensive and diversified knowledge of principles and practices in broad areas of assignments in their specialties and related fields. Makes decisions independently on engineering problems and methods and confers to resolve important questions and plan and coordinate work. Uses advanced techniques and modifies and extends theories, precepts, and practices in their field. Supervision and guidance relate primarily to objectives, critical issues, new concepts, and policy matters. Consulting with supervisors concerns unusual problems and developments.

The term of this appointment is 1 years, with the possibility of renewal based upon satisfactory performance and funding.

A remote work arrangement within the United States may be considered for candidates with the appropriate background and experience. University-paid business travel to Princeton, NJ may be required approximately 2-4 times per year.

Responsibilities

Lead the design, implementation and ongoing development of the Accelerator’s Data and Analytics Strategy with supporting architecture, programmes and training to help both members and researchers make best use of reliable and robust information and insight to inform the provision of sustainable services which provide best value for money and customer experience. Support the Director of Engineering and other members of the leadership team in developing the vision and priorities for the Accelerator and ensure best advice is provided on the most appropriate response to internal and external pressures for transformational change where digital and IT solutions are key to long term success. This postholder has a particular responsibility to ensure that decisions can be made after consideration of the best possible information so that they are based on evidence and insight. This information is also needed to create a performance framework which uses robust and up to date information so that resources can be realigned wherever necessary. Having the right digital architecture will be key both in having real time information and in dealing with performance at the right level. Deploy and maintain our data lake solution that will store and archive our data on an ongoing basis. This includes both planning of the storage, performance, optimization and cost tracking to ensure we keep our ongoing costs as optimal as possible Lead the team to
- Develop and maintain data pipelines to ingest, process, and analyze large volumes of data efficiently up to and beyond Petabyte scale
- Design and implement scalable distributed systems for data storage and processing.
- Optimize and tune data systems for performance and reliability.
- Implement realtime data processing of stream based data Mentors junior engineering team on day to day tasks.

Qualifications

- Proficiency in Python.
- Experience with distributed systems.
- Strong knowledge of data storage technologies; experience in data lakes and data mesh architectures is beneficial
- Familiarity with relational databases and Elasticsearch.
- Experience tuning data systems for performance and reliability.
- Development experience with PyTorch and TensorFlow on both CPU and GPU targets.
- Knowledge of text processing and image processing techniques.
- Experience with extracting data from API
- A combination of relevant work experience and education that would equal 10 years of relevant work experience with a record of accomplishment

- Experience with web scraping as well is also beneficial.

Princeton University is an and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law.

Standard Weekly Hours

36.25

Eligible for Overtime

No

Benefits Eligible

Yes

Probationary Period

180 days

Essential Services Personnel (see policy for detail)

No

Physical Capacity Exam Required

No

Valid Driver’s License Required

No

Experience Level

Mid-Senior Level #Ll-DP1

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