Data Architect

About the role

The role's responsibilities may include but are not limited to:

• Data Analysis: driving in-depth business data analysis to understand the origin, flow, level of detail, and meaning of data used to make decisions, as well as to identify both process-driven and system-driven data gaps or obstacles, along with recommended solutions.
• Data Requirements: proto-typing data/reporting solutions to drive a meeting of minds across multiple stakeholder groups so we can document and hand off fully vetted, implementable data requirements to IT development teams.
• Report + Report Dataset Development: designing, documenting, delivering innovative, configurable, highly supportable analytical reporting solutions based on standardized data definitions/practices and certified data sources established by IT.
• Data Quality + Governance: Partnering with IT, Data Governance, and subject matter experts to create and deploy effective data quality monitors and to advocate for strong data governance.
• Data Validation: Fully leading or supporting Test Lead in UAT Execution for newly developed or enhanced data integration and reporting solutions through orchestration with IT and subject matter experts.
• Production Support: establish and follow stabilization/production support SLA's for our team (reporting artifacts) and with IT for the underlying data infrastructure.
• Drive Data Integration and BI/reporting capabilities directly supporting program requirements.
• Data Architecture Strategy: Provide inputs to evolve team's data architecture and strategy aligned with business priorities and IT guardrails.

Responsibilities

The role's responsibilities may include but are not limited to:

• Data Analysis: driving in-depth business data analysis to understand the origin, flow, level of detail, and meaning of data used to make decisions, as well as to identify both process-driven and system-driven data gaps or obstacles, along with recommended solutions.
• Data Requirements: proto-typing data/reporting solutions to drive a meeting of minds across multiple stakeholder groups so we can document and hand off fully vetted, implementable data requirements to IT development teams.
• Report + Report Dataset Development: designing, documenting, delivering innovative, configurable, highly supportable analytical reporting solutions based on standardized data definitions/practices and certified data sources established by IT.
• Data Quality + Governance: Partnering with IT, Data Governance, and subject matter experts to create and deploy effective data quality monitors and to advocate for strong data governance.
• Data Validation: Fully leading or supporting Test Lead in UAT Execution for newly developed or enhanced data integration and reporting solutions through orchestration with IT and subject matter experts.
• Production Support: establish and follow stabilization/production support SLA's for our team (reporting artifacts) and with IT for the underlying data infrastructure.
• Drive Data Integration and BI/reporting capabilities directly supporting program requirements.
• Data Architecture Strategy: Provide inputs to evolve team's data architecture and strategy aligned with business priorities and IT guardrails.

Requirements

Minimum Qualifications:

• Bachelor's degree in Business Analytics, Information Systems, Supply Chain Management, or related field of study with 5+ years of relevant work experience.
• OR a Master's degree in the above fields with 3+ years of relevant work experience.
• Relevant work experience should include:
• Data visualization (Power BI)
• Query languages (e.g., SQL)
• Experience in Python, Advanced SQL, Azure, Snowflake, and/or Microsoft Fabric
• Experience in working with data used for demand planning, supply planning, procurement, sales and marketing, manufacturing, finance and/or product master data.

Qualifications

A Successful Candidate Will Demonstrate:

• A drive to investigate data through both people and systems/queries to achieve a comprehensive understanding.
• An affinity for leading in-depth conversations about data needs and usage and supporting this with active data analysis/experimentation to help teams formulate their data requirements as Intel transitions to Blue Yonder and SAP/S4 over the next several years.
• The willingness to effectively communicate with both technically minded IT engineers and business-focused subject matter experts.
• The willingness to proactively transform information into action.
• A tolerance for the ambiguity that comes with supporting large business and system transformation programs.
• Skills to analyze data requirements, and design effective database solutions and models, to store and retrieve company data.
• Data warehousing modelling and data integration design.