Data Engineering Manager - 339849

$125,000 - $217,500/Yr

PepsiCo - Plano, TX

Full-time - Mid Level

Hybrid - Plano, TX

Beverage and Tobacco Product Manufacturing

About the position

The Data Engineering Manager at PepsiCo is responsible for overseeing the development and operations of data products, leading a team of data engineers, and driving the vision for data engineering to positively impact the business. This role involves managing data pipelines, ensuring data quality, and collaborating with various stakeholders to enhance data accessibility and usability across the organization. The position requires a blend of technical expertise and leadership skills to foster innovation and support business objectives in a hybrid work environment.

Responsibilities

• Provide leadership and management to a team of data engineers, managing processes and their flow of work, vetting designs, and mentoring team members.
• 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 capture metrics and operational KPIs for data pipeline quality and performance.
• Implement best practices around systems integration, security, performance, and data management.
• Empower the business by creating value through increased adoption of data, data science, and business intelligence.
• 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 partners.
• Develop and optimize procedures to productionalize data science models.
• Define and manage SLAs for data products and processes running in production.
• Support large-scale experimentation done by data scientists.
• Prototype new approaches and build solutions at scale.
• Research state-of-the-art methodologies.
• Create documentation for learnings and knowledge transfer.
• Create and audit reusable packages or libraries.

Requirements

• 8+ years of overall technology experience, including at least 6+ years of hands-on data engineering, development, 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 including Python and PySpark.
• 4+ years of cloud data engineering experience in Azure.
• Fluent with Azure cloud service; 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 building high-volume ETL/ELT pipelines, data modeling, and data warehousing.
• Experience with Azure Data Factory, Azure Databricks, and Azure Machine Learning tools.
• Experience with data profiling and data quality tools like Apache Griffin, Deequ, and Great Expectations.
• Experience building/operating highly available, distributed systems for 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 cloud infrastructure and containerized services like Kubernetes.
• Experience with version control systems like GitHub and deployment/CI tools.
• Experience with Statistical/ML techniques is a plus.
• Experience with building solutions in the retail or 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 is required.

Nice-to-haves

• Experience with Statistical/ML techniques is a plus.
• Experience with building solutions in the retail or supply chain space is a plus.
• Understanding of metadata management, data lineage, and data glossaries is a plus.

Benefits

• Expected compensation range between $125,000 - $217,500, with a performance-based bonus target payout of 12% of annual salary.
• Paid time off including parental leave, vacation, sick leave, and bereavement.
• Comprehensive benefits package including Medical, Dental, Vision, Disability, Health, and Dependent Care Reimbursement Accounts, Employee Assistance Program (EAP), Insurance (Accident, Group Legal, Life), and Defined Contribution Retirement Plan.