Enterprise Data Operations Sr Analyst

Overview

As a member of the data engineering team, you will be the key technical expert developing and overseeing PepsiCos data product build & operations and drive a strong vision for how data engineering can proactively create a positive impact on the business. Youll be an empowered member of a team of data engineers who build data pipelines into various source systems, rest data on the PepsiCo Data Lake, and enable exploration and access for analytics, visualization, machine learning, and product development efforts across the company. As a member of the data engineering team, you will help lead the development of very large and complex data applications into public cloud environments directly impacting the design, architecture, and implementation of PepsiCos flagship data products around topics like customer orders, sales transformation, revenue management, supply chain, manufacturing, and logistics. You will work closely with process owners, product owners and business users. Youll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems.

Responsibilities

• Data pipeline development end-to-end, spanning data modeling, testing, scalability, operability and ongoing metrics.
• Data Integration with Data Science and Application team.
• Collaborate in architecture discussions and architectural decision making that is part of continually improving and expanding these platforms.
• Lead feature development in collaboration with other engineers; validate requirements / stories, assess current system capabilities, and decompose feature requirements into engineering tasks.
• Focus on delivering high quality data pipelines and tools through careful analysis of system capabilities and feature requests, peer reviews, test automation, and collaboration with other engineers.
• Develop software in short iterations to quickly add business value.
• Ensure that we build high quality software by reviewing peer code check-ins.
• Introduce new tools / practices to improve data and code quality; this includes researching / sourcing 3rd party tools and libraries, developing tools & frameworks in-house to improve workflow and quality for all data engineers.
• Support data pipelines developed by your team through good exception handling, monitoring, and when needed by debugging production issues.
• Support to attract talent to the team by networking with your peers, by representing PepsiCo HBS at conferences and other events, and by discussing our values and best practices when interviewing candidates.
  
  

• 7-10 years of overall technology experience, including at least 6+ years of hands-on experience in software development, data engineering, and systems architecture.
• 6+ years of experience in SQL performance tuning and optimization, including execution plan analysis, indexing strategies, and query refactoring.
• Strong experience in data modelling, data warehousing, and designing high-volume ETL/ELT pipelines using industry best practices.
• Proven ability to build and operate highly available, distributed systems for data ingestion, transformation, and processing of large-scale datasets (structured and semi-structured).
• 3+ years of experience working with Azure Databricks, including Delta Lake, Unity Catalog, and collaborative notebook development for data pipelines.
• Must have an understanding of medallion architecture.
• Proficiency with Apache Spark (PySpark/Scala), including tuning for performance, job optimization, and large-scale batch/stream processing.
• Experience integrating with Azure ecosystem services such as Azure Data Lake Storage (ADLS), Azure Synapse Analytics, Azure Data Factory, Azure Event Hub, Azure Data Explorer, Azure SQL and Azure Key Vault.
• Solid understanding of DevOps practices, including CI/CD pipelines for data engineering (e.g., using Azure DevOps or GitHub Actions).
• Experience participating in or leading architecture discussions and technical decision-making, especially in cloud-native data platform designs.
• Demonstrated experience in collaborating with data science and application engineering teams, ensuring seamless data integration and delivery.
• Proficiency in code review processes, version control (Git), and promoting a culture of clean, maintainable, and well-documented code.
  
  

• Tech/BE/M.Sc. in Computer Science, IT, or other technical fields.
  
  

• Excellent communication skills, both verbal and written, along with the ability to influence and demonstrate confidence in communications with senior level management.
• Proven track record of leading, mentoring data teams.
• Strong change manager. Comfortable with change, especially that which arises through company growth. Able to lead a team effectively through times of change.
• Ability to understand and translate business requirements into data and technical requirements.
• High degree of organization and ability to manage multiple, competing projects and priorities simultaneously.
• Positive and flexible attitude to enable adjusting to different needs in an ever-changing environment.
• Strong leadership, organizational and interpersonal skills; comfortable managing trade-offs.
• Foster a team culture of accountability, communication, and self-management.
• Proactively drives impact and engagement while bringing others along.
• Consistently attain/exceed individual and team goals
• Ability to lead others without direct authority in a matrixed environment.
  
  

• Highly influential and having the ability to educate challenging stakeholders on the role of data and its purpose in the business.
• Understands both the engineering and business side of the Data Products released.
• Places the user in the center of decision making.
• Teams up and collaborates for speed, agility, and innovation.
• Experience with and embraces agile methodologies.
• Strong negotiation and decision-making skill.
• Experience managing and working with globally distributed teams.