Data Architect- Sugar Land East Lawn
4 days ago
Internal Applicants: If you are a current associate of Prosperity Bank, please apply through the internal Talent - Career Center in ADP.
POSITION PURPOSE
The Data Architect documents Prosperity Bank's (the Bank) data assets, maps how data flows through its systems/applications, provides a blueprint for managing data, and ensures the data is managed properly to meet business needs for data. This role provides and promotes data architecture to cross-functional teams in the areas of data modeling, data discovery, data lineage, data access, etc.
The Data Architect will need to be well-versed in data management and data governance, as well as be able to effectively communicate and collaborate with multiple internal and external stakeholders. This role is also responsible for ensuring that sensitive data is accurately documented and appropriately secured, while being able to identify new technologies and solutions that can help improve data management practices across the Bank.
This role requires a variety of technical skills and ability to understand business needs, interact with business users to document business processes and existing data usage, and new data requirements.
This position will report directly to the Data Governance Manager.
ESSENTIAL DUTIES AND FUNCTIONS
This role is accountable for architecting the enterprise data with the below necessary duties:
- Establishes data architecture and evolves data model for the enterprise data to meet business needs
- Creates data flow diagrams, relationship diagrams between business entities, data objects and attributes
- Identifies and documents business processes, subprocesses, relationships by partnering with external providers, business partners, and IT teams
- Evaluates and assists in selecting the right data governance tools that align with Prosperity Bank's data infrastructure and strategy.
- Documents data collection processes, business applications, storage locations, and data standards, naming standards as per the data governance framework
- Tracks data flows, as well as data lifecycle and data lineage and helps the development of data definitions, business glossaries and data catalogs
- Owns technical efforts to implement and improve business performance through Data Architecture solutions and capabilities, such as master data management (MDM), metadata management, content management, data lineage, data integration, source of truth, and related data management or data infrastructure components
- Builds the artifacts necessary for data management such as data objects, data models, data lineage, glossary, and other artifacts
- Captures business rules, data definitions, and functional aspects accurately and appropriately within data models
- Establishes and follows standards and best practices that align with governance, data quality, and master data management initiatives, as well as roadmaps
- Engages with stakeholders to define data requirements and ensure that data models, standards, guidelines, and best practices support ease of data consumption
- Partners with data governance specialists to engage with business SMEs, data stewards in creation / maintenance of business glossary for the respective subject area and alignment with the enterprise
- Partners with the data quality specialists to provide data quality guidance and oversight, and to identify data architecture-related data quality improvements and drive back issues to the source system where appropriate
- Works with sensitive data management (SDM) Specialists and InfoSec team on SDM governance and security tools and processes, including data classification, sensitive data lineage, access controls, tagging, masking, and auditing
- Contributes in the technical creation of a master data strategy, related policies, master data model and appropriate technology
- Aids in the development of business cases, and ensures alignment with data management and governance initiatives
- Works collaboratively with peers and stakeholders across business and IT to influence technical and business projects to adopt data strategy and governance
- Aligns enterprise data policies and standards that govern how data is collected, integrated, transformed, and stored
- Drives enforcement of data governance policies related to data architecture and data business practices
- Helps evaluate data risks based on data governance program directives
- Enables audit controls for data validation and verification efforts
- Directs the regulatory compliance and security expectations, privacy laws for managing enterprise data
- Ensures that the data management practices are compliant with any applicable laws and/or regulations
- Defines and designs the data architecture framework, and guidelines to enable efficient and effective data management
- Collaborates with business, functional areas, and IT teams to ensure the alignment of data architecture with system and application design
- Works with business, functional, and technical partners to maintain conceptual, logical, and physical enterprise data models to support data needs
- Collaborates with business, functional, and IT teams to map current and target enterprise data view including documentation of source and destination of each step, and associated processes
- Provides guidance and supports data architecture and data governance-related matters
- Partners with business leaders, IT teams, data owners, and data stewards to understand data requirements and attain data governance objectives
- Designs and develops the overall data architecture to seamlessly incorporate data governance tools, ensuring that they enhance data handling processes without causing disruptions
- Integrates data governance tools with existing data management systems, allowing for the centralized control of data consistency, quality, and security
- Guides data stewardship activities, including metadata management, data lineage, and data quality assurance, data classification, master data management, and sensitive data management
- Partners with business and IT leaders to develop a holistic data collection and curation methodology, incorporating all sources of business data for analysis and reporting
- Improves the bank's business data landscape by owning the enterprise data model
- Documents data lineage across our business processes, identifying both value opportunities and potential data quality issues
- Assists and improves business data glossary and dictionary by working with the data governance office
- Partners with various Business, functional areas, and IT to provide options, recommendations, and assistance in brokering internal agreements regarding use and sharing of data (including associated access controls for sensitive data) across systems and groups.
- Defines technical standards and guidelines to promote reuse and interoperability of existing data stores, applications, and systems
- Helps design and develop standards, and procedures to ensure data quality, ingestion, curation, and provisioning of data to enable Data Governance and master data management (MDM)
- Analyzes, documents, and reports on any data-related problems or risks associated with the Bank's systems and data, present the findings and any potential solutions in a concise and organized manner to management
- Works with business, functional and IT teams to implement process and data controls to ensure compliance with various regulations and industry standards
- Reviews designs, existing quality plans, and data quality results to ensure that business solutions are sufficiently robust, stable, scalable, and compliant to meet regulatory requirements
- Leads, implementation and integration of data management governance tools
- Supports the newest technologies, regulations, and standards related to data governance
- Explores the value of enterprise data assets to drive the organization to be data centric
- Builds a community of best practice for data usage within the organization to help mature overall data literacy and competency
- Develops data training programs to ensure consistent use of organizational data and promote data awareness, literacy, and proficiency.
Education/Certification:
Bachelor's degree in Business, Finance, Marketing, Computer Science, or related field
Required Knowledge:
Familiarity with data management principles and practices in Data Management Body of Knowledge, 2nd Edition (DMBOK2)
Familiarity with data management frameworks such as DCAM
Knowledge of standards, and best practices prevalent in data governance, data management, data quality, and data privacy
Experience Required:- Minimum 6 years of business data and technology experience
- 5+ years of Experience of coordinating and implementing data architecture strategies with proven track record of implementing enterprise data standards and maturing capability to deliver advantage and enhance value delivery across a business
- 5+ years of advanced experience in building data models including robust data definitions, entity-relationship-attribute models, relational and/or dimensional models, as well as business system designs, data architecture, source to target mapping, and master data management
- 5+ years of advanced experience with Microsoft SQL stack and Python with the ability to write and understand complex programmable objects such as ETL/ELT and dynamic code frameworks
- 3+ years of experience designing and implementing complex, cross-departmental business measurement dashboards and performance scorecards
- 3+ years of experience with Tableau, Power BI, Enterprise Architect, Data Governance Suites, MDM systems, Data Catalog and Cloud environments
- 3+ years of experience in a highly regulated and data-centric industry such as financial services
- 2+ years of experience in banking and financial domain especially in deposits, loans will be a value add
- Strong understanding of enterprise architecture principles and frameworks, such as TOGAF or Zachman
- Demonstrated experience of cross-functional collaboration, relationship-building, networking, influencing, leadership, prioritization, and project management skills
- Proven experience in the design, and implementation of data governance platform strategies for operational, privacy, security, and other related control areas is a plus
- Experience in communicating complex concepts and business value in business terms or technical teams based on audience
- Advanced understanding of systems integrations and data integrations
- Excellent understanding current data trends and methodologies is required
- Excellent creative and practical problem-solving and issue-resolution skills
- Applies appropriate methodologies and SME knowledge to resolve complex business issues
- Experience in developing and maintaining detailed solution documentation
- Proven ability to learn new data technologies and frameworks
- Proven ability to partner across teams on system flows and design to delivery on new initiatives
- Demonstrated verbal and written communication skills, with ability to communicate effectively across different teams and levels of the organization to oversee projects beginning to end
- Collaborate with stakeholders to educate and influence on emerging technologies required to expand data ecosystem and functionality.
40 hours a week
- Establishes and follows standards and best practices that align with governance, data quality, and master data management initiatives, as well as roadmaps
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