Enterprise Data Operations Sr Analyst

Overview

This role is focused on leading a team of data engineers and/or fullstack development to design, develop, and manage scalable data pipelines and platforms while ensuring data quality, security, and performance. The position requires expertise in Azure Kubernetes Service (AKS), Python, Django, and GraphQL, along with experience in supply chain analytics, data modeling, and business intelligence. Responsibilities include mentoring engineers, collaborating with internal and external stakeholders, optimizing data workflows, and deploying machine learning models. The ideal candidate should have strong problem-solving skills, hands-on experience with structured and unstructured data, and proficiency in BI tools like Power BI and Tableau. This role plays a critical part in driving data adoption, automation, and innovation to support business intelligence and digital transformation initiatives.

Responsibilities

As a member of the data engineering team, you will be the key domain expert overseeing PepsiCo's business process and drive a strong discussion for how Supply Chain, Financial, Consumer, Channel, Category business needs to be defined and prioritize by working very closely with business leads, data science team and data engineering team. You'll develop an in-depth understanding of business processes in and translate business requirements to data engineering team in technical way. This role requires expertise in Azure Kubernetes Service (AKS) for managing and deploying containerized applications, along with strong proficiency in Python for data engineering tasks. Experience with Django is essential for building scalable web applications and APIs, while knowledge of GraphQL is needed for efficient data querying and integration. Additionally, the position demands leadership skills, proficiency in data pipeline management, system integration best practices, data security, and collaboration with data science teams to optimize and deploy models at scale. Strong problem-solving, automation, and monitoring capabilities are also critical for ensuring high-performance data infrastructure.

Qualifications

6+ years of experience with data analysis & data profiling in project, business requirements definition or data engineering in CPG or Manufacturing Industry.

5+ years work experience in the areas of Distribution Network Analysis, Manufacturing, Production Network Optimization, Transportation, Demand Planning, or other areas related to Supply Chain or other domains such as Financial, Consumer, Channel, Category etc.

4+ years of strong Data Profiling experience & ability to identify trends and anomalies in the data to in-form data model build out.

Experience in working with Datasets from POS Aggregators such as IRI, Nielsen, Kantar etc.

Experience working with structured/unstructured datasets, ability to clearly document and communicate requirement to technical team members.

Experience with Business Intelligence tools, SQLTools.

Experience with POS Aggregator Datasets such as IRI, Nielsen, Kantar, or similar, with a deep understanding of integrating and analyzing external market data for business insights.
Proficiency in Python and Django, with experience in developing and maintaining data-driven applications, APIs, and automation frameworks to streamline data workflows.

2+ Experience in GraphQL for building and optimizing data query layers, ensuring efficient data retrieval and seamless integration between systems.

4+ Expertise in Azure Kubernetes Service (AKS) for managing and deploying containerized applications and scalable data processing pipelines, ensuring high availability and performance.