Implement the data management framework at Kraft Heinz, ensuring data is organized, structured, easily accessible, secure, and aligned with strategic goals
Work cross-functionally with Product Owners, Business Stewards, Business Intelligence Engineers, Data Stewards, Data Scientists and end users to understand data consumers’ needs and solution requirements
Interact & influence business stakeholders to secure strong engagement and align data & analytical product delivery with strategic roadmaps
Design & contribute to the structure and layout of data lake house architecture, optimizing data storage, and establishing data access controls and security measures
Explore data sources by working with application owners to confirm datasets to be extracted
Contribute to establishing and implementing database structure, including schema design, table definitions, column specifications, and naming conventions
Document Data Architecture artifacts for different data products and solutions and perform peer review across various functions
Work closely with data stewards and governance functions to continuously improve data quality and enhance the reliability of data model(s)
Simplify existing data architecture, delivering reusable services and cost-saving opportunities in line with company policies and standards
Collaborate and contribute to the development and enhancement of standards, guidelines, and best practices within the Data Architecture discipline
Design and develop data products / data solutions within the commercial function supporting core sales datasets and downstream use cases leveraging internal and external data sources
Requirements
5+ years of experience in the design and implementation of scalable, high-performance, and reusable data models for enterprise-scale data warehousing
Experience translating business requirements into technical solution design & data architecture
Ability to navigate and collaborate with cross-functional teams involving data engineers, data scientists, business analysts, and stakeholders
Strong business process and functional understanding with an analytical background
Knowledge of Agile methodologies and experience working on tools such as Jira & Confluence
Proficient in the design and implementation of modern, cloud-based data analytics architectures
Expert-level SQL skills
Experience building enterprise data models (Logical, Physical, Conceptual ERD); data modeling tool experience a plus (ERWIN, ER/STUDIO, etc.)
Expertise in Snowflake or related cloud-based data warehousing tools (Databricks, Redshift, BigQuery, etc.)
Experience with enterprise-scale data engineering orchestration frameworks/ELT tools and common data engineering Python libraries (dbt, pandas, great expectations, etc.)
Proficient with business intelligence tools and technologies such as Power BI & Tableau
Benefits
Holistic wellness benefits* and perks
DCPP
VRSP
TFSA
Business Resource Groups (BRGs) to foster diversity, inclusion and belonging
Industry-leading total rewards package emphasizing a high discretionary bonus
Benefits begin immediately upon hire
Coverage for employees (and their eligible dependents) through affordable access to healthcare, protection, and saving for the future
Wellbeing events, resources, and learning opportunities
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
data management frameworkdata architecturedata modelingSQLcloud-based data analyticsdata warehousingdata engineeringdata lake house architecturedata access controlsdata quality
Soft skills
cross-functional collaborationstakeholder engagementanalytical skillsbusiness process understandinginfluencedocumentationpeer reviewproblem-solvingcommunicationorganizational skills