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Data Engineering Manager
| Company | PepsiCo |
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| Location | Plano, TX, USA |
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| Salary | $125000 – $217500 |
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| Type | Full-Time |
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| Degrees | |
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| Experience Level | Senior |
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Requirements
- 8+ years of overall technology experience that includes at least 6+ years of hands-on data engineering
- 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
- 4+ years in cloud data engineering experience in Azure
- Experience with Azure Data Factory, Azure Databricks and Azure Machine learning tools
- 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 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)
Responsibilities
- Provide leadership and management to a team of data engineers, while also being hand on coding, 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
- Support large-scale experimentation done by data scientists
- Prototype new approaches and build solutions at scale
- Research in state-of-the-art methodologies
- Create documentation for learnings and knowledge transfer
- Create and audit reusable packages or libraries
Preferred Qualifications
- 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
- Azure Certification is a plus
