Data Architect

Job description

Collaborates with teams to support seamless data accessibility while adhering to functional domain objectives

• Works with Product owners, Business stewards, Business Intelligence Engineers, Data Scientists and end users to understand data consumers' needs and develop data products/ data solutions within assigned sub-domain.
• Explores Data Sources by working with Application owners to confirm datasets to be extracted
• Designs Data models for Source data products and Master data products including schema design, table definitions, and column specifications.
• Designs and implements semantic models following established standards, supporting BI reporting, AI applications, and conversational analytics use cases.
• Documents Data Architecture artifacts for assigned data products
• Supports Data Engineering and BI Engineering teams during the build phase
• Participate in the peer review and quality assurance of project architectural artifacts across the Data Architecture group through governance forums
• Adopt and enforce the set standards, guidelines, and best practices established by Data Architecture chapter
• Design and develop data products / data solutions within the Finance Planning & Analysis subdomain under Finance domain supporting analytical and decision intelligence use cases that leverage a large variety of data sources from internal and external systems.
• Growing understanding of business processes and functional understanding with an analytical background.
• CPG experience with knowledge in domain specific concepts is beneficial
• Ability to navigate and collaborate with cross-functional teams involving data scientists, business analysts, and stakeholders
• Bachelor's degree in computer science, data science, engineering, or related field.
• Certifications in Data Management, Data Modelling and Cloud services are preferred.
• At least 3+ years of relevant experience in design and implementation of scalable, high-performance, and reusable data models that help in generating actionable insights.
• Strong background in data warehouse implementation.
• Experience in designing data models (Logical, Physical, Conceptual ERD) using data modeling tools (ERWIN, ER/STUDIO, etc.).
• Demonstrated ability to translate business requirements into technical solutions driving data architecture and Data Product design.
• Experience with enterprise-scale data engineering orchestration frameworks/ELT tools and common data engineering Python libraries (dbt, pandas, great expectations, etc.).
• Experience in designing semantic models for BI/AI data requirements
• Knowledge of Agile methodologies with experience working on tools such as Jira & Confluence.
• Strong Datawarehouse concepts and experience with data warehouse platforms such as Snowflake, HANA
• Experience with cloud services providers such as Azure
• Strong understanding of entity-relationship modeling, metadata systems, and data quality tools and techniques
• Extensive hands-on experience with enterprise data modeling (Logical, Physical, Conceptual ERD). Data modeling tool experience a plus (like ERWIN)
• Knowledge of ETL/ELT frameworks, tools and processes
• Understanding of Business intelligence tools and technologies such as Power BI
• Business Process and SAP functional understanding with an analytics background (preferred SAP ECC/S4, BW, HANA, BI, ARIBA experience) is a plus
• Understanding of Data Governance principles and practices including Data Quality, Data Security and Compliance
• Excellent communication and interpersonal skills for stakeholder management and cross-functional collaboration.