Principal Data Engineer, Manager

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

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 Data Management and 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.

Role summary:

As a Lead Data Engineer, you will be the key technical expert overseeing PepsiCo's data product build & operations and drive a strong vision for how data engineering can proactively create a positive impact on the business. You'll be empowered to create & lead a strong team of data engineers who build data pipelines into various source systems, rest data on the PepsiCo Data Lake, and enable exploration and access for analytics, visualization, machine learning, and product development efforts across the company.

What will you be doing more specifically:

• Provide leadership and management to a team of data engineers, managing processes and their flow of work, vetting their designs, and mentoring them to realize their full potential.
• Act as a subject matter expert across different digital projects.
• Oversee work with internal clients and external partners to structure and store data into unified taxonomies and link them together with standard identifiers.
• 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.
• Evolve the architectural capabilities and maturity of the data platform by engaging with enterprise architects and strategic internal and external partners.
• Develop and optimize procedures to “productionalize” data science models.
• Define and manage SLA’s for data products and processes running in production.
• Prototype new approaches and build solutions at scale.
• Create and audit reusable packages or libraries.

Qualifications/Requirements

• 8+ years of overall technology experience that includes at least 6+ years of hands-on software development, data engineering, and systems architecture.
• 6+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools.
• 6+ years of experience in SQL optimization and performance tuning, and development experience in programming languages like Python, PySpark, Scala etc.).
• 4+ years in cloud data engineering experience in at least one cloud (Azure, AWS, GCP).
• Fluent with Azure cloud services. Azure Certification is a plus.
• Experience scaling and managing a team of engineers.
• 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 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 or SnowFlake.
• Experience with running and scaling applications on the cloud infrastructure and containerized services like Kubernetes.
• Experience with version control systems like Github and deployment & CI tools.
• Experience with Azure Data Factory, Azure Databricks and Azure Machine learning tools.
• Experience with Statistical/ML techniques is a plus.
• Experience with building solutions in the retail or in the supply chain space is a plus
• Understanding 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.
• Proven track record of leading, mentoring, hiring and scaling 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.

Relocation Eligible: Eligible for Standard Relocation
Job Type: Regular