Greif is a global leader in performance packaging located in 40 countries. The company delivers trusted, innovative, and tailored solutions that support some of the world's most in demand and fastest-growing industries.
With a commitment to legendary customer service, operational excellence, and global sustainability, Greif packages life's essentials - and creates lasting value for its colleagues, customers, and other stakeholders.
Learn more about the company's Customized Polymer, Sustainable Fiber, Durable Metal, and Integrated Solutions at www.greif.com and follow Greif on Instagram and LinkedIn.
OUR VISION:
Being the customer service company in the world.
OUR PURPOSE:
Creating packaging solutions for life’s essentials.
Job Requisition #:
033238 Data Engineer (Open)
Job Description:
Greif is seeking a skilled Data Engineer to join our global data team in India. This role will be responsible for designing, developing, and supporting scalable data pipelines and data platform capabilities that improve data reliability, quality, and accessibility across the enterprise. In addition to core data engineering responsibilities, this position will support the enterprise data platform for traditional AI and GenAI use cases, including proofs of concept (PoCs) and pilot initiatives.
The Data Engineer will work closely with data scientists, architects, and analytics teams to ensure data is well-prepared, governed, and performant for AI experimentation and deployment. The role will collaborate with technology and business stakeholders across India, the US, and EMEA, providing both development and operational (administrative) support for enterprise data platforms.
Major Responsibilities
- Analyze, profile, and organize large volumes of structured and semi-structured data
- Design, develop, test, and maintain robust ETL/ELT pipelines using Azure Data Factory and Python
- Build and optimize data warehouse, data lake, and data platform solutions (e.g., Snowflake or similar platforms)
- Integrate and harmonize data from multiple internal and external sources
- Support data acquisition and ingestion strategies aligned with business and AI use-case needs
- Collaborate with AI Lab teams to prepare, curate, and optimize data sets for AI/ML as well as GenAI PoCs and pilot solutions
- Enable scalable and reusable data assets that support experimentation, feature development, and model training
- Evaluate business requirements and translate them into scalable data engineering and platform solutions
- Prepare data for descriptive, predictive, and prescriptive analytics
- Develop reusable data engineering frameworks, utilities, and analytical tools
- Collaborate closely with data scientists, data architects, BI developers, and business analysts
- Regularly interact with global stakeholders to identify opportunities to enhance analytics, AI, and data platform capabilities
- Proactively identify, troubleshoot, and resolve data quality, performance, and reliability issues
- Provide administrative and operational support for the data platform, including monitoring, access support, incident resolution, and basic platform maintenance
- Contribute to documentation, standards, and best practices for data engineering and AI-ready data platforms
- Perform other duties as assigned
Education and Experience:
- Bachelor’s degree in Computer Science, Data Analytics, or equivalent degree
- 3–5 years of hands-on experience as a Data Engineer or in a similar role
- Strong programming experience with Python
- Advanced SQL skills, including complex queries and performance tuning
- Hands-on experience with Snowflake or similar cloud data warehouses
- Experience supporting analytics and visualization tools such as Power BI (preferred), Tableau, or Cognos
- Good understanding of business domains such as Finance, Sales, Manufacturing, and Supply Chain
- Conceptual and practical understanding of data modeling, data integration, and data transformation techniques
- Experience with Microsoft Azure services, including Azure Data Factory, Azure Data Lake, Microsoft Fabric and related platform services
- Exposure to AI/ML workflows, feature engineering concepts, or data preparation for machine learning is a plus
- Relevant certifications (e.g., Snowflake Data Engineer, Azure Data Engineer) are desirable
Knowledge and Skills:
- Self-motivated with the ability to work independently in a global, matrixed environment
- Strong verbal and written communication skills, including the ability to explain technical concepts to non-technical stakeholders
- Demonstrates a strong sense of ownership, urgency, and accountability
- Comfortable supporting both stable production platforms and fast-paced AI PoCs/pilots
- Strong analytical and problem-solving skills
- Consistently exhibits a positive, proactive, and “can-do” attitude
At Greif, we believe that our colleagues are the center of our success. Our Total Rewards have a comprehensive focus on well-being and offer a competitive package that enables you to thrive, be engaged, and reach your full potential.
Protect Yourself From Scams: We value the integrity of our recruitment process and prioritize the well-being of our candidates. While you may find Greif job postings on various platforms, all legitimate opportunities can be verified on our official Careers page at www.greif.com. All communication from Greif regarding job opportunities will also come from an @greif.com email address. If you have concerns about the legitimacy of a job posting, receive an unsolicited job offer or suspect fraudulent activity, please contact us for verification via this link Contact Us - Greif.
EEO Statement:
https://www.greif.com/wp-content/uploads/2023/04/HR-101-Equal-Employment-Opportunity-Policy-English.pdf
We offer a competitive salary, excellent benefits and opportunity for growth. Greif is an equal opportunity employer. We will not discriminate against any applicant or employee on the basis of sex, race, religion, age, national origin, color, disability, veteran status or any other any other legally protected characteristic.
For more information read Greif’s Equal Opportunity Policy.
