R&D Data Expert and Analyst - Data Foundation

R&D SME data foundation Xops

Job Title: Xops Data foundation - R&D Data Expert / Analyst

Location: UniOps Bangalore, India 

About Hindustan Unilever Limited (HUL) 

HUL is India’s largest FMCG company, serving millions of consumers through iconic brands across Home Care, Beauty & Personal Care, and Foods & Refreshments. With a legacy of over 90 years, HUL is committed to making sustainable living commonplace. Our supply chain is the backbone of this mission, and digital transformation is key to driving agility, resilience, and cost efficiency. 

Be part of the world’s most successful, purpose-led business. Work with brands that are well-loved around the world, that improve the lives of our consumers and the communities around us. We promote innovation, big and small, to make our business win and grow; and we believe in business as a force for good. Unleash your curiosity, challenge ideas and disrupt processes; use your energy to make this happen. Our brilliant business leaders and colleagues provide mentorship and inspiration, so you can be at your best. Every day, nine out of ten Indian households use our products to feel good, look good and get more out of life – giving us a unique opportunity to build a brighter future.

Background:

Unilever R&D is transforming the way we innovate by embedding data and digital at the core of product development. We are looking for a passionate and technically skilled Data Subject Matter Expert (SME) to support our data and digital transformation agenda in R&D, SC verticals of Unilever

This role is open for internal candidates who want to contribute to building the next generation of data-driven R&D capabilities combined with SC data

Key Responsibilities:

• R&D Data Knowledge building: Act as the R&D data expert and point of contact for all data-related initiatives within the PLM space (e.g., formulation data, specifications, claims, and packaging) and help derive insights by combining R&D data with SC and Finance datasets.

• Business Collaboration: Able to collaborate with business users to understand requirements and convert that into functional specifications to build/enhance objects in UDL/BDL layers. SME should also be able to provide a high level effort estimates for BRDs

• Build Cycle: Update Design App and raise JIRA stories for UDL and BDL development, work with Build Factory team to implement the changes

• Data Pipeline Design & Operations: Design, develop, and support data pipelines to extract, transform, and load (ETL/ELT) data into the new harmonized data platform. Utilize Azure Data Factory (ADF) for orchestration (scheduling, workflow management) and Azure Databricks (Spark) for large scale data transformation and processing. Ensure pipelines are well-structured and efficient – including proper scheduling, error/exception handling, and data validation steps.

• Testing & Data Validation: Work with IT and testing teams during development and User Acceptance Testing (UAT) to validate the new data model and pipelines. Design test scenarios and sample data (including defining “golden records” or reference data sets) to verify that transformed data in the new system matches expected results.

• Go-Live Support / BAU Support: Provide support during deployment to ensure all critical data issues are resolved before go-live, so that business users can trust the new data platform from day one. Also, act as an SME and provide guidance & corrective steps if business users raise any issue on existing datasets.

• Data Governance & Quality: Uphold the organization’s data governance standards throughout the data transformation. Ensure consistent definitions and usage of data across the new model in line with enterprise data standards.

• Supporting AI initiatives: Lead efforts to digitize and structure complex scientific and formulation data for advanced analytics and AI/ML applications.

• Providing KT: Provide training and onboarding support to support / business teams on data tools, data best practices.

Required Qualifications & Experience:

• Bachelor's or Master’s degree in Data Science, Computer Science, Chemistry, or a related scientific or technical field.

• 5+ years of experience in data management / data modelling, with a strong track record of working with large data

• Prior experience and knowledge in Unilever R&D landscape, R&D datasets (Specification, Recipe, PIRD etc), functional knowledge of PLM, AWS and other major R&D source systems in Unilever is necessary

• Strong hands-on experience with modern data engineering tools and techniques using platforms such as Azure Data Factory (for ETL orchestration) and Azure Databricks (for data processing with Spark) is essential.

• Strong SQL skills and experience writing complex data transformation logic are required; experience with programming languages like Python or Scala for data engineering is a plus.

• Experience with data governance, data quality frameworks, and MDM in a scientific or regulated environment.

• Strong interpersonal and stakeholder engagement skills across technical and non-technical teams.

Preferred Skills:

• Experience in the FMCG or consumer goods sector.

• Exposure to cloud platforms (Azure preferred) and data lake architectures.

• Understanding of FAIR data principles and their application in R&D settings

Please Note:  All official offers from Unilever are issued only via our Applicant Tracking System (ATS). Offers from individuals or unofficial sources may be fraudulent—please verify before proceeding

Experience Level

Mid Level