Senior Analyst Data Engineer

Job Description

Role Overview:As a member of the data engineering team at PepsiCo, you will play a crucial role in developing and overseeing PepsiCos data product build & operations. Your primary focus will be on driving a strong vision for how data engineering can create a positive impact on the business. You will work alongside a team of data engineers to build data pipelines, enable exploration and access for analytics, visualization, machine learning, and product development efforts across the company. Your responsibilities will involve developing complex data applications in public cloud environments and collaborating closely with process owners, product owners, and business users.Key Responsibilities:- Actively contribute to code development in projects and services.- Manage and scale data pipelines from internal and external sources to support new product launches and ensure data quality.- Build and own automation and monitoring frameworks to 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 increasing the adoption of data, data science, and business intelligence landscape.- Collaborate with internal clients to drive solutioning and POC discussions.- Develop and optimize procedures to productionalize data science models.- Define and manage SLAs for data products and processes in production.- Support large-scale experimentation by data scientists.- Prototype new approaches and build solutions at scale.- Conduct research on state-of-the-art methodologies.- Create documentation for learnings and knowledge transfer.- Create and audit reusable packages or libraries.Qualifications:- 9 years of overall technology experience with at least 3 years in software development, data engineering, and systems architecture.- 3 years of experience in Data Lake Infrastructure, Data Warehousing, and Data Analytics tools.- 3 years of experience in SQL optimization, performance tuning, and programming languages like Python, PySpark, Scala, etc.- 2 years of experience in cloud data engineering with fluency in Azure cloud services. Azure Certification is a plus.- Experience with data modeling, data warehousing, and building high-volume ETL/ELT pipelines.- Experience with data profiling and data quality tools.- Experience with MPP database technology.- Experience with cloud infrastructure and containerized services.- Experience with version control systems and deployment tools.- Experience with Azure Data Factory, Azure Databricks, and Azure Machine Learning tools.- Experience with Statistical/ML techniques.- Experience in retail or supply chain space is a plus.- Understanding of metadata management, data lineage, and data glossaries.- Working knowledge of agile development, including DevOps and DataOps concepts.- Familiarity with business intelligence tools like PowerBI.(Note: The additional details about the company were not explicitly mentioned in the provided job description) Role Overview:As a member of the data engineering team at PepsiCo, you will play a crucial role in developing and overseeing PepsiCos data product build & operations. Your primary focus will be on driving a strong vision for how data engineering can create a positive impact on the business. You will work alongside a team of data engineers to build data pipelines, enable exploration and access for analytics, visualization, machine learning, and product development efforts across the company. Your responsibilities will involve developing complex data applications in public cloud environments and collaborating closely with process owners, product owners, and business users.Key Responsibilities:- Actively contribute to code development in projects and services.- Manage and scale data pipelines from internal and external sources to support new product launches and ensure data quality.- Build and own automation and monitoring frameworks to 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 increasing the adoption of data, data science, and business intelligence landscape.- Collaborate with internal clients to drive solutioning and POC discussions.- Develop and optimize procedures to productionalize data science models.- Define and manage SLAs for data products and processes in production.- Support large-scale experimentation by data scientists.- Prototype new approaches and build solutions at scale.- Conduct research on state-of-the-art methodologies.- Create documentation for learnings and knowledge transfer.- Create and audit reusable packages or libraries.Qualifications:- 9 years of overall technology experience with at least 3 years in software development, data engineering, and systems architecture.- 3 years

Keyskills :
PythonScalaData modelingKubernetesGithubRetailSupply chainMetadata managementAgile developmentDevOpsSQL optimizationPySparkAzure cloud servicesETLELT pipelinesMPP database technologyCloud infrastructureAzure Data FactoryAzure Databricks