Enterprise Data Operations Sr Analyst Job in Pepsico

Role Overview: Senior Data Engineer
As a Senior Data Engineer at PepsiCo, you will play a key role in driving the development and operations of PepsiCo's data infrastructure. You will lead the creation of scalable data pipelines and oversee data products that will directly impact business areas like revenue management, supply chain, manufacturing, and logistics. You will lead a team of data engineers who work with both on-premises and cloud-based systems, building solutions that enable data exploration, analytics, and machine learning across the company.

Key Responsibilities:

• Create reusable solutions to migrate data from legacy platforms like Teradata to Azure Databricks.
• Enable development by prioritizing code reuse, adopting test-driven development, and automating testing and monitoring for data pipelines.
• Build automation and monitoring frameworks to capture operational metrics and KPIs, ensuring data pipeline quality and performance.
• Implement best practices for systems integration, security, and performance in data management.
• Collaborate with internal teams (product, sector leads, data science) and external partners (SI partners/data providers) to define and clarify solution requirements.
• Work closely with enterprise architects to evolve the data platform architecture, ensuring it aligns with best practices and design standards.
• Define and manage service level agreements (SLAs) for data products and processes running in production.
• Support large-scale experiments conducted by data scientists.
• Prototype innovative solutions and scale them across the organization.
• Document learnings and conduct knowledge transfer to internal associates.

Qualifications:

• 9+ years of overall technology experience, including at least 4+ years in data engineering, software development, and systems architecture.
• 3+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools.
• 3+ years of experience with SQL optimization and performance tuning on MS SQL Server, Azure SQL, or other popular RDBMS.
• 3+ years of hands-on experience in Python and PySpark/Scala on big data platforms such as Databricks.
• 3+ years of cloud data engineering experience, with expertise in Azure or AWS.
• Strong knowledge of Azure cloud services (Azure Data Engineering certification is a plus).
• Experience integrating multi-cloud services with on-premises technologies.
• Preferred domain knowledge in the CPG industry, particularly in supply chain and Go-To-Market (GTM) operations.
• Proven experience in data modeling, building high-volume ETL/ELT pipelines, and working with data profiling tools like Great Expectations.
• Experience with MPP database technologies such as Databricks, Redshift, Synapse, or Snowflake.
• Familiarity with Kubernetes and scaling applications in cloud infrastructure.
• Experience with version control systems like ADO, GitHub, and CI/CD tools for deployment.
• Hands-on experience with Azure Data Factory, Azure Databricks, and Azure Machine Learning.
• Knowledge of Statistical/ML techniques is a plus.
• Experience with building solutions in retail or supply chain space is preferred.
• Understanding of metadata management, data lineage, and glossaries is a plus.
• Familiarity with Business Intelligence tools (e.g., PowerBI) is advantageous.
• A degree in Computer Science, Math, Physics, or related technical fields is required.

Work Schedule Flexibility:

• This position requires flexibility in working schedules. Candidates may work traditional Monday-to-Friday hours or alternative schedules such as Tuesday to Saturday or Sunday to Thursday, depending on project and coverage needs.

In-Office Requirement:

• Candidates are expected to be in the office at least 3 days a week. Specific in-office days should be coordinated with the immediate supervisor.

Additional Information:
At PepsiCo, we are committed to fostering a diverse and inclusive workplace. We are an equal opportunity employer, and we do not discriminate based on race, color, gender, age, national origin, religion, sexual orientation, gender identity or expression, marital status, citizenship, disability, HIV/AIDS status, or any other legally protected factor.