Enterprise Data Operations Senior Analyst

Duties: Design and implement scalable, enterprise-grade data pipelines for ingestion, transformation, and curation of structured and unstructured data into PepsiCo’s cloud-based Data Lake, leveraging Azure Data Factory, Databricks, DBT, and related tools. Lead the development and optimization of advanced ETL/ELT frameworks to support high-volume data workflows across hybrid cloud environments (on-premise and Azure), enabling efficient data access for analytics, business intelligence, and data science use cases. Establish and enforce best practices for data engineering operations, including monitoring, logging, alerting, and automated deployment using Azure DevOps, Git, and CI/CD pipelines to ensure data pipeline reliability and resilience. Ensure high performance and availability of data platforms by implementing performance tuning strategies across Delta Lake, Azure Synapse (Dedicated and Serverless Pool), and DB SQL, and managing data lineage, profiling, and quality controls. Drive enterprise data governance initiatives through the strategic implementation of Unity Catalog, enforcing fine-grained access controls, data classification policies, and metadata management standards to ensure data security and compliance. Establish best practices for coding documentation, foster reusable code libraries, standardize development practices, implement enterprise Agile delivery frameworks, and promote continuous learning by participating in global data engineering events. Apply in-depth knowledge of PepsiCo’s business operations, P&L structures, and Financial Planning and Analytics priorities to generate impactful insights and drive innovation. Collaborate with cross-functional teams to translate business needs into scalable data architectures and impactful technical solutions.

*Telecommuting permitted 50%: work may be performed within normal commuting distance from the PepsiCo office in Plano, Texas.

Job Requirements: Position requires a Bachelor’s degree (US or Foreign Equivalent) in Computer Science, Data Engineering, Information Technology, Analytics, Mathematics, Physics, or other technical fields and four (4) years of experience in hands-on software development, data engineering, data analytics, and systems architecture OR Master’s degree (US or Foreign Equivalent) in Computer Science, Data Engineering, Information Technology, Analytics, Mathematics, Physics, or other technical fields and two (2) years of experience in hands-on software development, data engineering, data analytics, and systems architecture. Must have four (4) years of experience (or 2 with Master’s) in: Strong programming expertise in Python, SQL, PySpark, SparkSQL development, and performance optimization for processing large-scale datasets. Must have two (2) years of experience with: working with cloud data platforms, including Azure Data Lake Storage Gen2, Azure Synapse Analytics, and Delta Lake; designing and implementing enterprise-scale ETL/ELT data pipelines using technologies Azure Data Factory, DBT, and Databricks Workflow; implementing CI/CD pipelines and system monitoring using platforms Azure DevOps, with strong familiarity in code version control tools Git; collaborating cross-functionally with business stakeholders and technical teams to deliver scalable, data-driven innovation; and demonstrated understanding of FMCG, P&L structures, Financial Planning and Analytics priorities, with a strong ability to translate business needs into actionable data solutions.

Salary: $118,893 - $148,000/ year.