Position Description:
Ameritas Investment Partners (AIP) is seeking a
Data Engineer Intern to contribute to data development and operation of an evolving Investment Data and Analytics ecosystem.This position will be responsible for contributing to the design, maintenance, and support of various data management activities in the AIP production environment. This is not a coding role with minimal people interaction. This position will be very communication heavy with plenty of stakeholder interaction where strong and clear communication skills will be critically important.
AIP is a registered investment advisor managing more than $23 billion in assets under management for insurance companies, public and private pension funds, endowments, foundations, mutual funds and high net worth individuals.
Position Location:
This is a hybrid role (Lincoln, NE) working partially in-office and partially from home.
Position Start Date:
This internship would begin as soon as possible.
What You Do:
- Design and configure data flows from automation to automated quality checks
- Identify, design, and implement internal process improvements, including automating manual processes, optimizing data delivery and more
- Build the infrastructure required for optimal extraction, transformation, and loading of data for consumption by portfolio managers and analysists
- Works with team to develop scalable, extensible solution architectures leveraging contemporary technologies in an evolving operational framework
- Participate in and help guide research of proof of concepts (POCs), including design, coding, and performance and efficacy measurement
What You Bring: - Actively enrolled at a college or university at least half-time as defined by your institution for the entire duration of the internship studying Computer Science, Computer Engineering, Information Technology, Management Information Systems, Statistics, or related field
- Ability to commit to a 12-month internship working full-time during the summer and part-time during the school year
- Full-time hours: 30-40 hours per week
- Part-time hours: 15-20 hours per week includes
- Must have a minimum GPA of 3.25
- Proficienct in Python and SQL preferred. Other technologies used:
- Data Quality & validation automation
- Amazon Web Services
- Bloomberg APIs
- Open Source Tools such as R
- MS.Net
- Splunk Machine Learning and/or Dataiku
- Must have at least a basic understanding of statistical concepts including percentiles, confidence intervals, correlation. Understanding of investment statistics such as beta, covariance a plus but not required.
- Strong interpersonal and professional skills, including the ability to ask thoughtful questions, communicate effectively, demonstrate punctuality, and consistently produce high-quality work.
- Desire to research and learn new technologies and frameworks including programming languages
- Exposure to RDMS and No-SQL type databases a plus
What We Offer
- Our company motto is “Fulfilling Life” and we take that job seriously, with a heavy commitment to volunteering and community support, employee well-being, and providing quality products and services that help our customers create a brighter future.
- Being a mutual-based organization, the return on our investment goes back into the company, to benefit our members/customers.
- We’re committed to professional development, opportunity, inclusion, and diversity. Team building and collaboration are also priorities.
An Equal Opportunity Employer:
Ameritas has a reputation as a company that cares, and because everyone should feel safe bringing their authentic, whole self to work, we’re committed to an inclusive culture and diverse workplace, enriched by our individual differences. We are an Equal Opportunity/Affirmative Action Employer that hires based on qualifications, positive attitude, and exemplary work ethic, regardless of sex, race, color, national origin, religion, age, disability, veteran status, genetic information, marital status, sexual orientation, gender identity or any other characteristic protected by law.
