Data Solution Architect, VP - Alpha Data Services
State Street
- Location
- Boston
- Employment
- Full Time
- Work model
- On-Site
- Level
- Staff
- Posted
- 21h ago
Skills
About this role
ADS Data Solutions Architect - VP Job Description State Street Alpha Data Services (ADS) is the data-as-a-service provider that is the back bone of the Alpha front to back strategy. Combining both technology and service provision to deliver significant data management value to our clients. We're looking for a candidate to take on the role of Data Solutions Architect supporting pre-sales due diligence and implementation. Why this role is important to us The team you will be joining is part of a global, cross-divisional group supporting State Street AlphaSM. State Street AlphaSM redefines the common definition of ‘alpha’ to mean powering better performance and outcomes at every point on the investment lifecycle and is the first open platform from a single provider that connects the front, middle and back office. It harmonizes data, technology and services across trusted providers to help our clients better manage their businesses. Join us if making your mark in an ever-changing, increasingly complex and competitive industry is a challenge you are up for. What you will be responsible for Be the face of the ADS organization to take the client’s Chief Data Architect and Data teams through the Alpha journey/adoption. Provide thought leadership to the client during the due diligence and through the entire implementation journey by understanding the Alpha architecture and client’s architecture. Responsible for the end to end solutioning of Front-to-Back ("F2B”) Alpha Data Platform (“ADP”)/ADS solutions to the client, starting with helping with pre contract due diligence and client presentations, documenting Target Data Solution Architecture and Future State Operating model of Data services, Solution Design, Environment Setup, Development of any Custom Components, Go Live activities and Post Go live hyper care support. Will manage the data solutioning and shared ownership of at least one large client implementation or multiple medium to small clients concurrently. Collaborate with upstream application and system owners within State Street to integrate into ADP using the standard model. Design and execution of process engineering to ‘bring to life’ the data solution encompassing data flows from multiple sources to target client consumption layer. Identify ADP product and data service gaps and partner with Product and Service Practice managers to solution the gaps and propose interim or tactical solutions. Partner with broader State Street Application/Service Owners to provide solutions in support of any new client requirements that are extension of the standard set of services or in some select cases a client specific bespoke data solution. Support the defect resolution process by collaborating with the development team in understanding the root cause of data issues and ensuring all defects are fixed. Collaborating with all internal technical and business teams including GTS, SaaS Ops, Alpha Cloud Ops, Alpha Platform Engineering, Alpha Product, ADS Implementation, Alpha Data Ops and clients to resolve issues. Collaborate with Client Implementation Executives and Leads to align on the Alpha implementation activities. Contribute to standard operating procedures and ensure adoption, including any client specific requirements that might be custom bespoke processes. Engage with the L2/L4 Support teams to ensure proper coverage. Collaborate with external vendors as needed for a given client implementation, this will include vendors like Bloomberg, Refinitive, MSCI, Factset, Axioma etc. These skills will help you succeed in this role: Demonstrate excellent communication skills across all channels and levels of recipients including team members, colleagues, clients at all levels including C suite. Experienced hands-on ETL, Snowflake, CI/CD Pipelines, SQL, Data Quality rules and Data-Readiness design and implementation of data platforms Experience in designing and implementing relational data models for a variety of