PepsiCo | Hiring | Architect, ML Ops Engineer | BigDataKB.com | 1/13/2022

Purpose:
This role will assist with defining architecture of Machine Learning / Artificial Intelligence / Advanced Analytics solutions. In this capacity, this role will work with our lead AI solution architect in partnering with other development teams in designing or validating architecture designs for solutions,

This role will also work to create an advanced analytics innovation pipeline for new methods and techniques to be integrated in future solutions. Will collaborate with the CTO Innovation team in onboarding and designing solutions to be industrialized and will also help with creation of advanced analytics materials and training.

Accountabilities:

• Help gather requirements from multiple stakeholders to get sufficient information to create solution architecture and designs for digital solutions in the machine learning and AI space
• Identify patterns for reuse in future solutions across multiple types of assets, from solution approaches, ML models, data transformation code
• Collaborate with other team members to extract reusable code and elements, refactor them and maintain a reusable catalog.
• Create an formalize an analytics innovation pipeline and collaborate with the organization to implement new technologies, types of ML models, etc

Years of Experience:

• 11+ years of IT experience
• 3+ years of work experience in an Analytics Cloud Engineer role in Azure platform
• At least 2+ years of hands on experience Architecting and Delivering solutions using the Azure Data Analytics platform
• At least 4 years of data science experience

Mandatory Techincal skills:

• Azure: Production experience in Azure, Azure storage, ADLS, Azure ML, Azure IOT, Data Factory setup & monitoring pipelines, Azure Databricks, Azure SQL/DWH, AAS, PowerBI, App Services, Functions; Infra steps, such as PowerShell scripting for scripted deployments
• Data engineering: Data parsing, cleansing, quality checks, pipeline scripting, archival etc.
• Stream-processing systems: Structured streaming, Spark-Streaming
• Scripting/Programming: Unix/Linux and shell scripting, Python, PySpark/Scala
• SQL: SQL queries and related technologies.
• Strong Analytical skills

Nice to Have

• Azure Kubernetes service, Azure Container Instances, Azure DevOps
• Exposure to Big Data Analytics (data and technologies), Data Sciences, predictive analytics, modelling, machine learning, in-memory applications
• Understanding of DevOps, Containerization / Docker images, Flask, cloud deployments
• Data modeling experience in Data warehouse and DataMart
• Exposure to PowerBI development or other visualization platforms
• Certification in MS Azure

Mandatory non-technical skills:

• Strong communications and organizational skills with the ability to deal with ambiguity while juggling multiple priorities and projects at the same time
• Should be able to work independently
• Experience supporting and working with cross-functional teams in a dynamic environment.
• Prior experience in working in Scaled Agile framework

Differentiating competencies:
Ability to work with virtual teams (remote work locations); lead team of technical resources based in multiple locations across geographies
Participate in ideation and solutioning discussions, driving clarity of complex issues/requirements to build robust solutions

Purpose:
This role will assist with defining architecture of Machine Learning / Artificial Intelligence / Advanced Analytics solutions. In this capacity, this role will work with our lead AI solution architect in partnering with other development teams in designing or validating architecture designs for solutions,

This role will also work to create an advanced analytics innovation pipeline for new methods and techniques to be integrated in future solutions. Will collaborate with the CTO Innovation team in onboarding and designing solutions to be industrialized and will also help with creation of advanced analytics materials and training.

Accountabilities:

• Help gather requirements from multiple stakeholders to get sufficient information to create solution architecture and designs for digital solutions in the machine learning and AI space
• Identify patterns for reuse in future solutions across multiple types of assets, from solution approaches, ML models, data transformation code
• Collaborate with other team members to extract reusable code and elements, refactor them and maintain a reusable catalog.
• Create an formalize an analytics innovation pipeline and collaborate with the organization to implement new technologies, types of ML models, etc

Years of Experience:

• 11+ years of IT experience
• 3+ years of work experience in an Analytics Cloud Engineer role in Azure platform
• At least 2+ years of hands on experience Architecting and Delivering solutions using the Azure Data Analytics platform
• At least 4 years of data science experience

Mandatory Techincal skills:

• Azure: Production experience in Azure, Azure storage, ADLS, Azure ML, Azure IOT, Data Factory setup & monitoring pipelines, Azure Databricks, Azure SQL/DWH, AAS, PowerBI, App Services, Functions; Infra steps, such as PowerShell scripting for scripted deployments
• Data engineering: Data parsing, cleansing, quality checks, pipeline scripting, archival etc.
• Stream-processing systems: Structured streaming, Spark-Streaming
• Scripting/Programming: Unix/Linux and shell scripting, Python, PySpark/Scala
• SQL: SQL queries and related technologies.
• Strong Analytical skills

Nice to Have

• Azure Kubernetes service, Azure Container Instances, Azure DevOps
• Exposure to Big Data Analytics (data and technologies), Data Sciences, predictive analytics, modelling, machine learning, in-memory applications
• Understanding of DevOps, Containerization / Docker images, Flask, cloud deployments
• Data modeling experience in Data warehouse and DataMart
• Exposure to PowerBI development or other visualization platforms
• Certification in MS Azure

Mandatory non-technical skills:

• Strong communications and organizational skills with the ability to deal with ambiguity while juggling multiple priorities and projects at the same time
• Should be able to work independently
• Experience supporting and working with cross-functional teams in a dynamic environment.
• Prior experience in working in Scaled Agile framework

Differentiating competencies:
Ability to work with virtual teams (remote work locations); lead team of technical resources based in multiple locations across geographies
Participate in ideation and solutioning discussions, driving clarity of complex issues/requirements to build robust solutions