Über diese Data Solution Architect Principal Stelle bei M&T Bank
OVERVIEW:
The Wilmington Trust Institutional Services (IS) division is experiencing rapid business growth and has initiated a strategic program of continuous improvement to support the growth objectives. The goals of the program are to reduce operational issues and risks by standardizing processes, implementing best-practices in key areas, and adding new governance and control functions. In addition, long term digital transformation is required to grow revenue through new and transformed digital-first trust and agency service products, to move from a product-centric to client-centric operating model, to move from market-specific to global solutions, and to dramatically lower the cost to serve. These two strategic focus areas are driving growth in overall business investment.
Institutional Services is advancing a strategic platform initiative to simplify and standardize transaction management across the full lifecycle, from onboarding through ongoing administration. A strong data architecture will provide the trusted, consistent, and scalable foundation needed to strengthen controls, improve the user experience, and support future growth.
JOB SUMMARY:
In alignment with IS’s growing investment, we are looking for a senior Data Solution Architect who can translate complex business processes into a scalable, governed, and implementable data architecture. Who can provide guidance that supports the development of a key strategic platform that integrates data from disparate systems to drive business solutions. Plan and designs solutions that are cost-effective, compliant with enterprise policies and corporate technology standards and align with business and technology strategies. Is a key resource in helping to set the technology direction for Data.
This role is a senior data architecture role responsible for shaping strategy, translating strategy into detailed solution designs, and guiding implementation teams through delivery. The role is not intended to perform data engineering build work or application development; it defines the architecture, data models, data contracts, governance requirements, integration patterns, and implementation-ready design artifacts that delivery teams use to build the solution.
POSITION RESPONSIBILITIES:
- Lead the technical design and data integration for a highly complex data project involving multiple technologies that integrates data across multiple domains.
- Work with the business to understand requirements and develop conceptual, logical, and physical data models.
- Produces data artifacts such data dictionaries, source to record matrices, data flow diagrams, data lineage documentation.
- Create API Schema and transition state architecture.
- Produce the design artifacts that account for different data frequencies and ensure Service Level Agreements (SLA) are documented and accounted for in the design.
- Identify any strategy gaps in solution and work with team members and senior management to develop plans to rectify gaps.
- Assess existing systems, data structures and integrations, identify duplication or gaps, and define a phased path to the target architecture.
- Create a data governance framework for the new solution, including data quality rules, and audit requirements.
- Ensure designs are cloud-ready and portable with minimum rework by documenting any transition state architecture and incorporating multi cloud components.
- Work with the agile team to ensure the documented best practices are used in data platform development and address identified training gaps.
- Establish non-functional standards in designs; design, refactor, optimize and establish interaction of multiple flexible frameworks to maximize reusability across value chain capabilities to streamline efficiencies.
- Work with the agile team, technology leads, and senior management in release train discussions to determine key dependencies for stories and align solutions to add business value.
- Help in the establishment of data architecture standards and ensure they are met across releases.
- Understand and adhere to the Company’s risk and regulatory standards, policies and controls in accordance with the Company’s Risk Appetite. Identify risk-related issues needing escalation to management.
- Identify risk-related issues needing escalation to management
- Promote an environment that supports belonging and reflects the M&T Bank brand.
- Maintain M&T internal control standards, including timely implementation of internal and external audit points together with any issues raised by external regulators as applicable.
- Complete other related duties as assigned.
MINIMUM QUALIFICATIONS REQUIRED:
- Bachelor’s degree and a minimum of 9 years related experience, or in lieu of a degree, a combined minimum of 13 years higher education and/ or work experience, including a minimum of 9 years related experience
- Experience with leading an initiative that spans across multiple technology practices and business verticals
- Experience creating componentized scalable designs
- Experience in driving the design, refactor and optimization of frameworks
- Experience with multiple programming languages and tools and how they integrate
- Experience in containerization technologies
- Experience implementing scalable designs on at least one mainstream cloud provider platform
- Experience implementing data architecture and integration concepts
IDEAL QUALIFICATIONS PREFERRED:
- Minimum of 7 years of data solution architecture experience, including experience defining target-state and transition-state architecture for complex enterprise platforms.
- Experience implementing initiatives that have impact enterprise wide
- The Open Group Architecture Framework (TOGAF), Cloud Solution Architecture on Azure, Amazon Web Services (AWS) and/or Google Cloud Platform (GCP) Certification
- Experience in pertinent data modeling platforms
- Experience with multiple Not Only Structured Query Language (NoSQL) platforms
- Experience with data lake and data warehousing design
- Experience with real time data processing and high-volume low latency systems
- Experience defining conceptual, logical and physical data models
- Ability to establish authoritative data sources, ownership and lineage
- Ability to rationalize data across multiple legacy platforms
- Experience designing canonical data models and reusable API data contracts
- Experience defining data-quality, reconciliation and audit requirements
- Experience creating phased transition plans from current- to future-state architecture
- Working across business, product, architecture and engineering teams
