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Senior Enterprise Data Architect
at Webster Bank
436 Slater Road-HF308
If you're looking for a meaningful career, you'll find it here at Webster. Founded in 1935 by Harold Webster Smith, our focus has always been to put people first--doing whatever we can to help individuals, families and businesses achieve their financial goals. And while we've grown into a leading commercial bank, we remain passionate about serving our customers, supporting our communities, and making a difference in people's lives. We can make a difference in your life, too. By empowering you to build the meaningful career you've been looking for.
Responsibility, respect, trust, teamwork and citizenship are the values on which Webster was founded. Together we call them The Webster Way, and they are what set us apart as a bank and an employer. Guided by these values, we put people first - working hard to live up to our customers, and each other, every day.
The Senior Enterprise Data Architect will provide expertise in data analysis, design, deploying and management of organization's data architecture. The Data Architect will be responsible for defining how the company's structured and unstructured data will be stored, consumed, integrated/shared and reported by different IT application systems. The data architect will define and align architecture principles to the overarching enterprise architecture principles.
- Build an enterprise model, a central dictionary of standard common business vocabulary, define strategy/ approach & principles for data quality management, master data management, data integration, data security/access and data archiving & retention.
- Extend the data architecture to acquire streaming and cloud-born external data.
- Modernize the data integration layer by enabling greater data delivery styles.
- Develop a virtualized data organization layer to connect to data as well as collect it.
- Develop a comprehensive analytics environment that spans from traditional reporting to prescriptive analytics.
- Determine overall modeling standards, guidelines, best practices and approved modeling techniques and approaches.
- Supervise the creation of all physical and logical data models in the organization.
- Supervise the data modeling staff
- Participate in due diligence of new software purchases by reviewing all proposed data models contained in packaged or commercially available applications..
- Serve on data integration, business intelligence and content management competency panels or teams.
- Participate in all data integration and enterprise information management (EIM) programs and projects -- both enterprise and point-to-point efforts -- by rationalizing data processing for reusable module development.
- Work jointly with the data services administrator in developing the data objects and data models to support data services under a service-oriented architecture approach.
- Establish and manage the metadata management approach for the organization.
- Supervise the data administration team (modeling, metadata managers and end-user query optimization).
- Support the maturity and adoption of the EIM program across the organization.
Job Skills / Knowledge:
- minimum of fifteen years of related experience as a data architect highly desirable, demonstrating hands-on experience in enterprise data architecture, data warehousing, data modeling and/or data analysis.
- Familiarity with data science concepts, as well as MDM, business intelligence, and data warehouse design and implementation techniques.
- Ability to relate architectural decisions and recommendations to business needs. Experience developing reference architecture, principles and standards.
- Strong analytical and problem-solving skills.
- Ability to communicate across all levels of the organization and work with diverse project teams.
- Ability to speak and present to business executives in a business and professional consultative manner
- Experience with distributed management and analytics in cloud and hybrid environments.
- An understanding of a variety of data access and analytics approaches (for example, microservices and event-based architectures).
- Experience with database technologies (e.g., SQL, NoSQL, Oracle, Hadoop, Teradata)
- Experience with Tableau, SAS, Business Objects and other business intelligence tools.