Principal Data Engineer - Tech Lead
The Role
The Advanced Strategies & Research Technology Team in Fidelity's Asset Management organization is an embedded team passionate about unlocking the potential of new technologies, techniques and datasets, to assist our Investment Professionals in generating alpha for our investment products and customers.
The role is ideal for someone with an enterprise development background, with a strong technology, coding and data skills, looking to operate in a less constrained environment, as part of an accelerated development team.
The role is ideal for a skilled technical leader with strong design, teamwork and influencing skills.
Ideally the candidate is a Full Stack, but this role will be primarily focused on processing and generating Analytics from structured and unstructured datasets with the ability of parallel processing potentially in the cloud.
The ideal candidate will quickly adapt to new technologies and a go-getter, with quantitative concepts and data.
The Team
The team is comprised of a diverse set of technology professionals including application developers, database engineers, data scientists and tool prototypes with quantitative backgrounds who work collectively with our business partners to take ideas from a whiteboard, through prototypes that garner feedback to be rapidly deployed to our users, all the way through to integration with enterprise applications both on prem and on the cloud.
THE EXPERTISE WE'RE LOOKING FOR
- Bachelor's or Master's Degree in a technology related field (e.g. Engineering, Computer Science, etc.) required.
- 10+ years of enterprise development and a desire to work on a fast-paced development team
- Experience of balancing multiple tracks concurrently
- Experience in planning, designing, leading, and executing technical solutions and improvements
- Experience with object orientated programming, with projects completed using many of the following technologies including Java or C#, Python, Angular 2.0+, AWS, and RDBMS
- Knowledge of Cloud computing concepts (AWS) and using CI/CD tools
- Strong problem-solving and troubleshooting skills with on call responsibilities
- You have a track record of engineering experience by processing large datasets and building scalable applications and Rapid Prototyping
- You have a background with enterprise development and a consistent record rapidly bring projects from inception to delivery in ambitious timeframes. Using Java or C#, Python, Angular 2.0+, MVC frameworks
- You have solid experience in Object Oriented Programming in Java or C# or Python
- You have solid experience in developing custom Data Pipelines to extract data, map data, transform data, and to load data in various data stores like RDBMS, Oracle, S3, PL/SQL, and / or shared drives.
- You have solid experience in Python and libraries such as Pandas / Numpy, etc. or Spark
- You are familiar with extracting data from REST APIs and parallel processing large datasets using C# or Java
- Your demonstrable experience developing scripting in Linux and Windows
- Experience with migrating applications to AWS (Cloud) will be an added advantage.
Company Overview
At Fidelity, we are passionate about making our financial expertise broadly accessible and effective in helping people live the lives they want! We are a privately held company that places a high degree of value in creating and nurturing a work environment that attracts the best talent and reflects our commitment to our associates. We are proud of our diverse and inclusive workplace where we respect and value our associate for their unique perspectives and experiences. For information about working at Fidelity, visit FidelityCareers.com. Fidelity Investments is an equal opportunity employer.
Fidelity will reasonably accommodate applicants with disabilities who need adjustments in order to complete the application or interview process. Please email us at accommodations@fmr.com or call 800-835-5099, prompt 2, option 2 if you would like to request an accommodation.
Certifications:
Category:
Information Technology