Kraft Heinz

Senior – Data Architect

India · Work style not stated · Full time

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About the role

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EmployerKraft Heinz
LocationIndia
Work styleWork style not stated
Employment typeFull time
Employer posted9 Sep 2026

Job Description

SENIOR DATA ARCHITECT

Finance, Master Data & S4

Kraft Heinz | Enterprise Data & Analytics

Function

Enterprise Data & Analytics / IT

Reports To

Group Lead Data Products & Platforms

POSITION OVERVIEW

The Senior Data Architect – S/4HANA Analytics owns the design, governance, and quality of domain-specific data assets that power analytics and decision intelligence at Kraft Heinz. Operating at the intersection of SAP S/4HANA, Finance, and modern data engineering, this role leads data architecture execution across global S/4 implementation and rollout programs, establishing scalable data products and enterprise data models that serve Finance, Supply Chain, Procurement, Manufacturing, and adjacent business domains.

The role collaborates closely with Product Owners, Business Stewards, BI Engineers, Data Scientists, and Data Engineers to translate complex business requirements into trusted, governed, and reusable data solutions — from source-system ingestion through consumption-ready data products.

Show full description

KEY RESPONSIBILITIES

Lead data architecture execution for global S/4HANA implementation and rollout programs, ensuring seamless integration of data standards across countries and business units.
Define and own the enterprise data architecture for S/4HANA analytics, including Medallion Architecture (Bronze / Silver / Gold) design across ELT tooling and cloud platforms.
Serve as the data architecture authority for Finance initiatives — including GL, Cost Center / Profit Center Accounting, CFIN, and financial reporting hierarchies (HRRP tables).
Design conceptual, logical, and physical data models (ERDs) for source data products — covering schema design, table definitions, and column specifications.
Build scalable data models that support BI, advanced analytics, and AI/ML workloads across Finance, Supply Chain, and Global Operations domains.
Partner with application owners to analyze and evaluate data sources, ensuring alignment with architectural standards and extraction requirements.
Design and develop Finance and Global Operations data products supporting analytical and decision intelligence use cases leveraging diverse internal and external data sources.
Work with Product Owners, Business Stewards, BI Engineers, Data Scientists, and end users to understand data consumers’ needs and translate them into well-defined data products and solutions.
Assess domain feasibility requirements and translate business requirements into actionable data architecture and data product designs.
Engage cross-functional teams — including data scientists, business analysts, and functional leads — throughout the full data product lifecycle.
Support Data Engineering and BI Engineering teams during the build phase, providing architectural guidance and technical direction.
Review data model development, validate designs, participate in Integration Test Cycles and User Acceptance testing, and provide deployment approval.
Work closely with Data Stewards to enforce data governance, security, data quality, and compliance requirements for assigned data assets.
Participate in peer review and quality assurance of architectural artifacts across the Data Architecture group through governance forums.
Document data architecture artifacts for data products and solutions; perform peer review across functions.
Collaborate with the Data Architecture chapter to develop, maintain, and enhance data standards, modeling guidelines, and architectural best practices.
Contribute to the continuous improvement of reusable frameworks, patterns, and templates within the enterprise data architecture practice.

QUALIFICATIONS

Education

Bachelor’s degree in computer science, Data Science, Engineering, or a related technical field.
Relevant certifications: Azure Fundamentals, Snowflake, CDMP, or equivalent cloud/data platform credentials are advantageous.

Experience

5+ years of experience designing and implementing scalable, high-performance, and reusable data models that drive actionable business insights.
Strong background in SAP S/4HANA implementation and rollout programs, with solid understanding of Finance business processes including financial reporting, planning, and analytics.
Proven expertise in enterprise data warehouse architecture, design, and implementation.
Hands-on experience developing Conceptual, Logical, and Physical Data Models and ERDs using industry-standard tools such as ERwin, ER/Studio, or equivalent.
Demonstrated ability to translate business requirements into technical data architecture solutions and data product designs.
Strong SQL skills with working knowledge of cloud data platforms (Azure) and modern data warehouses (Snowflake, HANA).
Experience with modern data engineering frameworks and ELT/ETL technologies — including dbt, Python,
CPG (Consumer Packaged Goods) industry experience with domain-specific knowledge is a plus.

Technical Skills

SAP S/4HANA: CDS Views, SLT, SAP Datasphere.
Data warehousing & platforms: Snowflake, SAP HANA, or equivalent cloud data platforms.
Data modeling tools: ERwin, ER/Studio, or equivalent; strong hands-on experience with Logical, Physical, and Conceptual ERD design.
BI & Reporting: Power BI or equivalent reporting and visualization tools.
Cloud platforms: Azure (preferred)

CORE COMPETENCIES

Technical Architecture

Designs scalable, governed data models and end-to-end data flows across SAP S/4HANA and cloud platforms.

Business Acumen

Translates complex Finance and CPG business requirements into practical, trusted data products and analytics solutions.

Stakeholder Collaboration

Builds strong relationships with Product Owners, Engineers, Data Stewards, and business stakeholders across global teams.

Data Governance Mindset

Champions data quality, lineage, metadata standards, and security as foundational to analytics trustworthiness.

Delivery Focus

Drives data architecture from requirements through deployment, supporting testing cycles and governance checkpoints.

Continuous Improvement

Proactively refines standards, patterns, and best practices within the Data Architecture chapter.

Location(s)

Bengaluru - Brookfield GCC

Kraft Heinz is an Equal Opportunity Employer – Underrepresented Ethnic Minority Groups/Women/Veterans/Individuals with Disabilities/Sexual Orientation/Gender Identity and other protected classes.

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