Enterprise Data Operations Assoc Manager

Enterprise Data Operations Assoc Manager

Requirements

• 8+ years of overall technology experience that includes at least 5+ years of hands-on software development, data engineering, and systems architecture.
• 5+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools.
• 5+ years of experience developing enterprise data models.
• Experience in at least one of data modeling tool (ER/Studio, Erwin) for three years.
• 5+ years in cloud data engineering experience in at least one cloud (Azure, AWS, GCP).
• Experience with data modeling, data warehousing, and building high-volume ETL/ELT pipelines.
• 5+ years of experience in developing programs for high volume ETL/ELT pipelines using Spark, Hadoop.
• 3+ years of hands-on experience on-premises to cloud migrations, adept in planning, execution, and optimization of end-to-end data migration projects.
• Experience with integration of multi cloud services with on-premises technologies.
• Experience with building solutions in the retail or in the supply chain space is preferred.
• 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, BigQuery or SnowFlake.
• Experience with running and scaling applications on the cloud infrastructure and containerized services like Docker and Kubernetes.
• Experience with version control systems like Azure DevOps, and deployment & CI tools.
• Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus.
• Experience in building API services with high volume is preferred.
• Certified in Data engineering/Analytics in one or more clouds (AWS, GCP, Azure) is preferred.
• Experience in infrastructure automation using Infrastructure as a Service (IAAS) tools such as Terraform.
• Experience with building Data Observability systems.
• Proficient in designing, implementing, and managing infrastructure code for efficient and scalable deployment of resources.
• Experience with metadata management, data lineage, and data glossaries.
• Working knowledge of agile development, including DevOps and DataOps concepts.
• Familiarity with business intelligence tools (such as PowerBI/Tableau).
• BA/BS in Computer Science.

Responsibilities

• Oversee PepsiCo’s data product build & operations and drive a strong vision for how data engineering can proactively create a positive impact on the business.
• Lead the development of very large and complex data applications into public cloud environments directly impacting the design, architecture, and implementation of PepsiCo’s flagship data products around topics like revenue management, supply chain, manufacturing, and logistics.
• Work with business users, data product owners, platform owners, enterprise architects, data management owners, and data engineering teams to ensure the data supply chain and the enterprise data products are built with high performance, high availability, and maintainability standards using current and emerging big data technologies.
• Establish data design patterns that will drive flexible, scalable, and efficient data models to maximize value and reuse.
• Make tactical architecture decisions to support immediate projects and inform long term data architecture strategy.

Preferred Qualifications

• Experience with building solutions in the retail or in the supply chain space is preferred.
• Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus.
• Experience in building API services with high volume is preferred.
• Certified in Data engineering/Analytics in one or more clouds (AWS, GCP, Azure) is preferred.