Enterprise Data Operations Sr Analyst

Responsibilities: #LI-Hybrid

Locations: Barcelona, Spain; Vitoria-Gasteiz, Spain

PepsiCo is using the power of data to transform the way our world-famous portfolio of brands are sold every day. Our Data Science & Analytics group influences every aspect of how we sell and move our products. In just a short period of time, they’ve built new capabilities that have defined the data science roadmap across all of our brands. Members of our team solve complex problems facing our rapidly changing business and get to see their work come to life in the real world.

Join PepsiCo’s Enterprise Data Operations team which develops quality data collection processes, maintains the integrity of our data foundations and enables business leaders and data scientists across the company to have rapid access to the data they need for decision-making and innovation.

As a Data Modeling Specialist, 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 a key technical expert performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architects teams.

**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.
- 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 mínimal 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**:

- 5+ years of overall technology experience that includes at least 3+ years of data modeling and system architecture.
- 3+ years of experience developing enterprise data models.
- Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models).
- 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 with building solutions in the retail or in the supply chain space 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.
- 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.
- Ability to understand and translate business requirements into data and technical requirements.
- Positive and flexible attitude to enable adjusting to different needs in an ever-c