Sr. Data Analyst, Data Engineering

Job Description

Role Overview:You will be a key technical expert as a member of PepsiCos Data Management and Operations team, responsible for developing quality data collection processes, maintaining data integrity, and enabling access to data for decision-making and innovation. As a member of the data engineering team, you will drive a strong vision for how data engineering can positively impact the business by overseeing data product build & operations. Your role will involve building data pipelines, enabling data exploration and access, and leading the development of complex data applications.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 for systems integration, security, performance, and data management- Empower the business through increased adoption of data, data science, and business intelligence- Collaborate with internal clients to drive solutioning and proof of concept discussions- Develop and optimize procedures to operationalize 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- Research state-of-the-art methodologies- Create documentation for learnings and knowledge transfer- Create and audit reusable packages or librariesQualifications Required:- 4 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 such as Python, PySpark, Scala, etc.- 2 years of cloud data engineering experience in Azure, with fluency in Azure cloud services- Experience with multi-cloud services integration and on-premises technologies- Proficiency in 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- Familiarity with MPP database technologies such as Redshift, Synapse, or SnowFlake- Experience in running and scaling applications on cloud infrastructure and containerized services like Kubernetes- Proficiency in version control systems like Github and deployment & CI tools- Experience with Azure Data Factory, Azure Databricks, and Azure Machine learning tools is a plus- Familiarity with Statistical/ML techniques, retail, or supply chain solutions- Understanding of metadata management, data lineage, and data glossaries- Working knowledge of agile development, including DevOps and DataOps concepts- Proficiency in business intelligence tools like PowerBI- BA/BS in Computer Science, Math, Physics, or other technical fieldsAdditional Details:Omit this section as there are no additional details of the company present in the job description. Role Overview:You will be a key technical expert as a member of PepsiCos Data Management and Operations team, responsible for developing quality data collection processes, maintaining data integrity, and enabling access to data for decision-making and innovation. As a member of the data engineering team, you will drive a strong vision for how data engineering can positively impact the business by overseeing data product build & operations. Your role will involve building data pipelines, enabling data exploration and access, and leading the development of complex data applications.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 for systems integration, security, performance, and data management- Empower the business through increased adoption of data, data science, and business intelligence- Collaborate with internal clients to drive solutioning and proof of concept discussions- Develop and optimize procedures to operationalize 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- Research state-of-the-art methodologies- Create documentation for learnings and knowledge transfer- Create and audit reusable packages or librariesQualifications Required:- 4 years of overall technology experience with at least 3 years in software development, d

Keyskills :
Software DevelopmentData EngineeringPythonScalaData ModelingData ExtractionData ProcessingMetadata ManagementAgile DevelopmentDevOpsBusiness Intelligence ToolsSystems ArchitectureSQL OptimizationPySparkCloud Data EngineeringAzure Cloud Serv