Although not a household name, State Street is one of the world’s largest and most important financial services institutions, providing round-the-clock services to the global investment community. We touch $33 trillion in assets every day, and are the world’s third largest investment manager ...
Although not a household name, State Street is one of the world’s largest and most important financial services institutions, providing round-the-clock services to the global investment community. We touch $33 trillion in assets every day, and are the world’s third largest investment manager with over $2.8 trillion in assets under management. To do this we manage as much data as one of the internet giants on nearly as large a technical footprint.
In January 2018, we launched one of the industry’s largest technical transformation projects, in effect building a new bank from the ground up. This project isn’t greenfield in the way most banks claim projects to be; we’ve started with a blank sheet of paper both operationally and technically. We use the same technologies that Silicon Valley giants are using. We deploy to multiple public clouds as well as building our own private cloud to achieve even better performance. We push out microservices into what will be one of the largest Kubernetes installations in the world and leverage immutable storage to process and store hundreds of terabytes of data per day. We are transforming our industry through the application of distributed ledger technology and cognitive computing while we are key contributors in the open source communities driving our systems.
This isn’t a traditional banking role. This is a chance to push your technical skills with people more comfortable in a technology firm than an investment bank by solving real problems that affect anyone with any form of savings worldwide.
This role is for the technology team that is in charge of our Data Analytics. This is a major component of the technology transformation program which is building a new application operating system for State Street, covering everything that an application DevOps team would work with on a daily basis:
- We provide analytics sandbox environments allowing teams to analyze data at scale using the best tools for the task.
- We capture the exploratory analytics processes and create managed batch and streaming processes.
- We create and apply analysis to deliver insight, reports and visualizations internally and to our customers.
- We use the latest technology to create cloud native applications for ingesting, transforming, retrieving, analyzing, processing, auditing and securing data for use internally and by our customers.
- We leverage cloud infrastructure to deliver elastic, highly available, scalable and resilient systems.
- We provide a consistent, managed, globally addressable view of data and integrate attribute based access control across data at rest, in motion and operation.
- We use and contribute to open source technologies ensuring we have access to the most efficient tools for a given task.
- We rely upon Kubernetes as a microservices architecture and “kubectl as a service” across public and private clouds.
- We manage everything else in our common Kubernetes infrastructure, including package management, networking & service mesh.
- We provide standard infrastructure for both telemetry and log management, all the way through to application tracing and dashboards.
- We provide standard CI/CD infrastructure.
- We operate in an evolving environment where new technology and processes are rapidly adopted without losing quality.
- We develop application archetypes & training materials and assist application developers in making the best use of this infrastructure.
- We do all this in a true DevOps fashion with agile infrastructure and a follow-the-sun mandate.
- We are a geographically distributed team, including fully remote workers.
We are looking for a strong Data Scientists & Data Engineers to join our Data Analytics team.
- You will work with other members of your team to investigate feature requests, perform detailed analysis, create specifications, build, test and implement new functionality.
- You will diagnose and correct problems in live infrastructure in support of our production clients.
- You will leverage frameworks, tools & automation to ensure quality software deliveries.
- You will help standardize on key monitoring metrics and alerts that will drive the DevOps nature of the team.
- You will support a follow-the-sun operations approach, working with colleagues across three continents.
- You will work in an agile way, using agile development and infrastructure techniques.
- You will collaborate with your peers across the transformation effort ensuring that best practices are followed throughout the organization.
- You will mentor and assist in training more junior members of your team including recent graduates.
- You will be an active member in the Open Source communities surrounding the technologies that we use on a daily basis.
Successful candidates will have the following skillset:
- A degree in computer science or related computational discipline or equivalent experience acquired on the job.
- Demonstrable experience in working on production-grade systems.
- Ability to learn about new technology innovation and creativity in applying it to business problems.
- Have the ability to communicate effectively in English both writing and speaking, and the ability to communicate technical subjects effectively through diagramming.
- Appreciate the value diversity (in all its forms) brings to our team and company.
- If your experience is more in data science we expect you will know at least one of our key programming languages: Spark, Python, R and have a track record of using it at scale to deliver insight or analysis.
- If your experience is more in data engineering, we expect you will have familiarity with tools in the Hadoop ecosystem in particular Spark, PySpark, RSpark as well as D3, SQL, NoSQL, etc.
- Experience with Kafka, streaming analytics and event sourcing.
- The ideal candidate will have mix of data analysis, data engineering and data visualization.
- Experience in working on an Open Source project.
- Experience working in a financial services environment is a plus, but not a must-have requirement.