Data Solutions Architect

Job Summary:

The Data Solutions Architect is responsible for architecting data solutions utilizing their vast experience in data architecture standards and processes. They will develop artifacts such as enterprise data models, product life-cycle metrics and value proposition, and assist business and IT leaders with application rationalization, measuring total cost of ownership, developing architecture roadmaps, and prioritizing global domain initiatives in collaboration with the data product leadership team. The Data Solutions Architect is a key member of Vantive's Global Data Engineering and Analytics Platforms team and leads the Data and Analytics Architecture working in close collaboration with the Data CoE, business domains and data product delivery.

Key Experiences & Attributes:

Bachelor's or Master's degree in Information Technology or a related field

10+ years of experience designing, developing, and delivering data solutions

Extensive background in mapping Enterprise vision and mission into data domain architecture models and creating value proposition in the use of data as a key asset to make decisions.

5+ years of experience in establishing and running data architecture practice for large enterprises

Ability to rapidly define target architectures in line with modern architecture & design best practices

Strong understanding of the software development life cycle models including working in an Agile organization

Demonstrated capability to quickly adapt to and leverage new technologies, platforms, and methodologies.

Foundational understanding of the key principles of architecture designs.

Experience in a customer-facing role such as technical support, consulting or solutions architecture.

Familiarity with data models and industry data standards such as automation and agile architecture.

Strong communication skills.

Negotiation skills, long term, and strategic thinking without losing the actual needs, teamwork and fast integration into bigger teams.

Understanding of regulated Healthcare industry, GDPR, and other global data privacy design controls

Excellent written and oral communication skills

Responsibilities:

Enterprise Data Architecture

Own the domain data models.

Design data solutions based on business needs

Advise, mentor and assist data engineering teams on the best data architecture approaches to solve business problems

Partner with Data Governance team to ensure the interoperability between the data maintained in the data platforms and the Master Data and metadata collections.

Partner with the Enterprise Data Architect to ensure all Non-Functional Requirements (e.g., security, performance, availability, privacy, scalability, compliance etc.) are addressed in the data products developed.

Evaluate, prototype, test and recommend emerging data technologies and platforms from open source or vendors.

Lead or participate in data domain efforts to build proof of concept prototypes

Communicate complex technical topics to non-technical business users

Define data architecture framework and methodology for assessing the health of the data products

Define data architecture patterns and framework, develop standards for using modern data platforms and data pipelines, and take ownership to define and maintain enterprise data models.

Create and implement a multi-year plan that supports the organization's data centric vision via technology enablers.

Guide the organization-wide adoption and help to increase the data architecture maturity

Solution Architecture

Provide guidance related to cross-functional digital product standards as applied throughout the product delivery teams

Domain experience in one or more functional areas:

oSupply Chain

oCommercial

oCorporate Functions (Finance, Legal, HR, Procurement)

oDigital Product Innovation (R&D)

Provide leadership and cross-functional digital product standards as applied throughout the product delivery teams

Technology liaison between business stakeholder/product owner and development team

Support for critical issues with the data solutions (including performance and data quality issues)

Define Metrics and KPIs that measure the effectiveness of the data solutions in the business domain

Strong understanding of the software development life cycle models including working in an Agile organization

Experience in negotiation and communication at a leadership level

Strong organizational skills, project and time management skills, and multi-tasking abilities