Senior Data Engineer

Overview:
**Are you ready to drive PepsiCo’s digital evolution and accelerate transformation across our global operations?**

PepsiCo operates in a fast-changing environment where big data and digital technologies are driving business transformation. Our Data Management and Operations team plays a critical role in building and maintaining high-quality data foundations that power business insights, advanced analytics, and innovation in areas like eCommerce, IoT, and mobile experiences. By ensuring seamless data collection, standardization, and accessibility across the company, we empower business leaders and data scientists with the insights they need to drive impactful decisions.

As a **Data Engineer at PepsiCo**, you will be a key technical expert responsible for developing and managing data products that directly impact critical business areas such as revenue management, supply chain, manufacturing, and logistics. You will design and build complex data pipelines, integrate diverse data sources into the PepsiCo Data Lake, and enable analytics, machine learning, and product development at scale. Working in a hybrid environment across cloud and on-premise systems, you’ll collaborate closely with process owners and business users to shape the future of PepsiCo’s data ecosystem.

**Responsibilities**:
**Your day to day with us**:

- Active contributor to code development in projects and services.
- Manage and scale data pipelines from internal and external data sources to support new product launches and drive data quality across data products.
- Build and own the automation and monitoring frameworks that captures metrics and operational KPIs for data pipeline quality and performance.
- Responsible for implementing best practices around systems integration, security, performance and data management.
- Empower the business by creating value through the increased adoption of data, data science and business intelligence landscape.
- Collaborate with internal clients (data science and product teams) to drive solutioning and POC discussions.
- Develop and optimize procedures to “productionalize” data science models.
- Define and manage SLA’s for data products and processes running in production.
- Support large-scale experimentation done by data scientists.
- Prototype new approaches and build solutions at scale.
- Create documentation for learnings and knowledge transfer.
- Create and audit reusable packages or libraries.

Qualifications:
**What you will need to succeed**:

- 4+ years of overall technology experience that includes at least 3+ years of hands-on software development, data engineering, and systems architecture.
- 3+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools.
- 3+ years of experience in SQL optimization and performance tuning, and development experience in programming languages like Python, PySpark, Scala etc.).
- 2+ years in cloud data engineering experience in Azure.
- Fluent with Azure cloud services. Azure Certification is a plus.
- Experience with integration of multi cloud services with on-premises technologies.
- Experience with data modeling, data warehousing, and building high-volume ETL/ELT pipelines.
- 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 or SnowFlake.
- Experience with version control systems like Github and deployment & CI tools.
- Working knowledge of agile development, including DevOps and DataOps concepts.

**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.
- 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.

**What makes us different?**
- Hybrid work model: combination of remote and collaborative office experience to enable innovation
- Entrepreneurial environment in leading international company
- Professional growth possibilities & learning opportunities
- Variety