Job Description

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Overview

Main purpose:

PepsiCo operates in an environment undergoing immense and rapid change. Big-data and digital technologies are driving business transformation that is unlocking new capabilities and business innovations in areas like eCommerce, mobile experiences and IoT. The key to winning in these areas is being able to leverage enterprise data foundations built on PepsiCo's global business scale to enable business insights, advanced analytics and new product development. PepsiCo's Data Management and Operations team is tasked with the responsibility of developing quality data collection processes, maintaining the integrity of our data foundations and enabling business leaders and data scientists across the company to have rapid access to the data they need for decision-making and innovation.

What PepsiCo Data Management and Operations does:

• Maintain a predictable, transparent, global operating rhythm that ensures always-on access to high-quality data for stakeholders across the company
• Responsible for day-to-day data collection, transportation, maintenance/curation and access to the PepsiCo corporate data asset
• Work cross-functionally across the enterprise to centralize data and standardize it for use by business, data science or other stakeholders
• Increase awareness about available data and democratize access to it across the company

As Senior Analyst , Data Modeling, your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analyzing project data needs, identifying data storage and integration needs/issues, and driving opportunities for data model reuse, satisfying project requirements. Role will advocate Enterprise Architecture, Data Design, and D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architects teams.

As a member of the data modeling team, you will create data models for very large and complex data applications in public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics. The primary responsibilities of this role are to work with data product owners, data management owners, and data engineering teams to create physical and logical data models with an extensible philosophy to support future, unknown use cases with minimal rework.. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. You will establish data design patterns that will drive flexible, scalable, and efficient data models to maximize value and reuse.
Responsibilities

Key Accountabilities:

• Complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, EMR, Spark, DataBricks, Snowflake, Azure Synapse or other Cloud data warehousing technologies.
• Governs data design/modeling - documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned.
• Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting.
• Supports assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices, and tools.
• Contributes to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development.
• Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework.
• Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives, maximizes reuse.
• Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper management: business and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations.
• Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development.
• Assist with data planning, sourcing, collection, profiling, and transformation.
• Create Source To Target Mappings for ETL and BI developers.
• Show expertise for data at all levels: low-latency, relational, and unstructured data stores; analytical and data lakes; data streaming (consumption/production), data in-transit.
• Develop reusable data models based on cloud-centric, code-first approaches to data management and cleansing.
• Partner with the Data Governance team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders.
• Support data lineage and mapping of source system data to canonical data stores for research, analysis and productization

Qualifications

Qualifications:

• 8+ years of overall technology experience that includes at least 4+ years of data modeling and systems architecture.
• 3+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools
• 4+ years of experience developing enterprise data models.
• Experience in building solutions in the retail or in the supply chain space.

• Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models).
• Experience with integration of multi cloud services (Azure) with on-premises technologies.
• Experience with data profiling and data quality tools like Apache Griffin, Deequ, and Great Expectations.
• Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets.
• Experience with at least one MPP database technology such as Redshift, Synapse, Teradata or SnowFlake.
• Experience with version control systems like Github and deployment & CI tools.
• Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus.
• Experience of metadata management, data lineage, and data glossaries is a plus.
• Working knowledge of agile development, including DevOps and DataOps concepts.
• Familiarity with business intelligence tools (such as PowerBI).
• BA/BS in Computer Science, Math, Physics, or other technical fields.

Skills, Abilities, Knowledge:

• Excellent communication skills, both verbal and written, along with the ability to influence and demonstrate confidence in communications with senior level management.
• Comfortable with change, especially that which arises through company growth.
• 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.
• Good and interpersonal skills; comfortable managing trade-offs.
• Foster a team culture of accountability, communication, and self-management.
• Consistently attain/exceed individual and team goals

Differentiating Competencies Required:

• Ability to work with virtual teams (remote work locations )
• Contribute to technical discussions, driving clarity of complex issues/requirements to build robust solutions
• Strong communication skills to meet with business, understand sometimes ambiguous, needs, and translate to clear, aligned requirements
• Able to work independently with business partners to understand requirements quickly, perform analysis and lead the design review sessions.
• Places the user in the center of decision making.
• Teams up and collaborates for speed, agility, and innovation.
• Experience with and embraces agile methodologies.
• Experience working with globally distributed teams.