15 Systems Architecture Jobs

Overview As Senior Analyst, Data Modeling, your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analyzing project data needs, identifying data storage and integration needs/issues, and driving opportunities for data model reuse, satisfying project requirements. Role will advocate Enterprise Architecture, Data Design, and D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architects teams. As a member of the data modeling team, you will create data models for very large and complex data applications in 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. The primary responsibilities of this role are to work with data product owners, data management owners, and data engineering teams to create physical and logical data models with an extensible philosophy to support future, unknown use cases with minimal rework. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. You will establish data design patterns that will drive flexible, scalable, and efficient data models to maximize value and reuse. Responsibilities Complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, EMR, Spark, DataBricks, Snowflake, Azure Synapse or other Cloud data warehousing technologies. Governs data design/modeling documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned. Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting. Supports assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices, and tools. Contributes to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development. Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework. Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives, maximizes reuse. Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper management: business and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations. Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development. Assist with data planning, sourcing, collection, profiling, and transformation. Create Source To Target Mappings for ETL and BI developers. Show expertise for data at all levels: low-latency, relational, and unstructured data stores; analytical and data lakes; data str/cleansing. Partner with the Data Governance team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders. Support data lineage and mapping of source system data to canonical data stores for research, analysis and productization. Qualifications 8+ years of overall technology experience that includes at least 4+ years of data modeling and systems architecture. 3+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 4+ years of experience developing enterprise data models. Experience in building solutions in the retail or in the supply chain space. Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models). Experience with integration of multi cloud services (Azure) with on-premises technologies. 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, Teradata or SnowFlake. Experience with version control systems like Github and deployment & CI tools. Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus. Experience 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).

Overview As a member of the data engineering team, you will be the key technical expert developing and overseeing PepsiCo's data product build & operations and drive a strong vision for how data engineering can proactively create a positive impact on the business. You'll be an empowered member of a team of data engineers who build data pipelines into various source systems, rest data on the PepsiCo Data Lake, and enable exploration and access for analytics, visualization, machine learning, and product development efforts across the company. As a member of the data engineering team, you will help 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. You will work closely with process owners, product owners and business users. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. Responsibilities Be a founding member of the data engineering team. Help to attract talent to the team by networking with your peers, by representing PepsiCo HBS at conferences and other events, and by discussing our values and best practices when interviewing candidates. Own data pipeline development end-to-end, spanning data modeling, testing, scalability, operability and ongoing metrics. Ensure that we build high quality software by reviewing peer code check-ins. Define best practices for product development, engineering, and coding as part of a world class engineering team. Collaborate in architecture discussions and architectural decision making that is part of continually improving and expanding these platforms. Lead feature development in collaboration with other engineers; validate requirements / stories, assess current system capabilities, and decompose feature requirements into engineering tasks. Focus on delivering high quality data pipelines and tools through careful analysis of system capabilities and feature requests, peer reviews, test automation, and collaboration with other engineers. Develop software in short iterations to quickly add business value. Introduce new tools / practices to improve data and code quality; this includes researching / sourcing 3rd party tools and libraries, as well as developing tools in-house to improve workflow and quality for all data engineers. Support data pipelines developed by your teamthrough good exception handling, monitoring, and when needed by debugging production issues. Qualifications 6-9 years of overall technology experience that includes at least 5+ years of hands-on software development, data engineering, and systems architecture. 4+ years of experience in SQL optimization and performance tuning Experience with data modeling, data warehousing, and building high-volume ETL/ELT pipelines. Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets. Experience with data profiling and data quality tools like Apache Griffin, Deequ, or Great Expectations. Current skills in following technologies: Python Orchestration platforms: Airflow, Luigi, Databricks, or similar Relational databases: Postgres, MySQL, or equivalents MPP data systems: Snowflake, Redshift, Synapse, or similar Cloud platforms: AWS, Azure, or similar Version control (e.g., GitHub) and familiarity with deployment, CI/CD tools. Fluent with Agile processes and tools such as Jira or Pivotal Tracker Experience with running and scaling applications on the cloud infrastructure and containerized services like Kubernetes is a plus. Understanding of metadata management, data lineage, and data glossaries is a plus.

Required Qualifications: Bachelors or Masters degree in Electrical Engineering, Computer Engineering, or related field with 15 years or more relevant experience. Experience with use-case analysis and decomposition. Experience in Linux, Zephyr, Free RTOS or similar operating systems. Strong understanding of microprocessor and micro controller architectures, including CPU cores , DSP, memory management, and peripheral integration. Experience with system level performance optimization, low-power design, SW/HW co-design , and real-time processing. Familiarity with high-speed interconnects, memory architectures, DDR, PCIe, and bus protocols. Strong collaboration skills to work across multidisciplinary teams, including silicon, software, hardware, board design, and validation engineers. Experience in product development processes. Preferred Qualifications: Experience with ARM Cortex and/or RISC-V architecture. Experience with media processing, vision and imaging applications. Experience with system-level simulation tools, hardware/software co-design, and debugging techniques. Familiarity with Machine Learning Hardware IPs, tools, and architecture. Knowledge of functional safety and security standards. Familiarity with Wi-Fi integration, networking protocols, and secure wireless communication.

Required Qualifications: Bachelors or Masters degree in Electrical Engineering, Computer Engineering, or related field with 15 years or more relevant experience. Experience with use-case analysis and decomposition. Experience in Linux, Zephyr, Free RTOS or similar operating systems. Strong understanding of microprocessor and micro controller architectures, including CPU cores , DSP, memory management, and peripheral integration. Experience with system level performance optimization, low-power design, SW/HW co-design , and real-time processing. Familiarity with high-speed interconnects, memory architectures, DDR, PCIe, and bus protocols. Strong collaboration skills to work across multidisciplinary teams, including silicon, software, hardware, board design, and validation engineers. Experience in product development processes. Preferred Qualifications: Experience with ARM Cortex and/or RISC-V architecture. Experience with media processing, vision and imaging applications. Experience with system-level simulation tools, hardware/software co-design, and debugging techniques. Familiarity with Machine Learning Hardware IPs, tools, and architecture. Knowledge of functional safety and security standards. Familiarity with Wi-Fi integration, networking protocols, and secure wireless communication.

ROLES AND RESPONSIBILITIES: Good understanding of LCS (Life Cycle Services) and Azure DevOps. D365 and Azure installation and configuration. Dynamics 365 for Finance and Operations Services, including Installation, Upgrade, Patching and Maintenance, Backup, Restore across DEV, Sandbox and Production environments. Knowledge with Dynamics 365 architecture (CRM and Finance & Operations) Background in Development, Systems Architecture, and/or Operations. Experience with Azure Active Directory and Enterprise Application Integrations. Working experience with Team Foundation Server (TFS and VSTS) Experience with software build and deploy tools (Microsoft Releases). Experience in Automated Deployments with Continuous Integration workflows. Knowledge of Continuous Delivery and Continuous Deployment workflows Installation of Team Foundation Server /D365 Finops and SQL Server. Instillation of Client Pre-Requirements and Software Installations. Installation and Configuration of Terminal Server. Installation of Windows server Operating Systems (2012 and above) Assists in the planning, design, documentation, and implementation of various systems to include desktop PCs, servers, network equipment, and software applications. Develops, maintains, and monitors procedures for all server backups. Monitors, plans, and coordinates the distribution of client/server software and service packs. Makes recommendations for new equipment and services to purchase and works with various vendors for procurement. Perform on-site and remote technical support. Assist in the organization and inventory of all hardware and software resources. Creates and maintains good technical documentation. Performs other duties as assigned. Designs, installs, upgrades, configure, and repairs local and wide area network hardware and infrastructure.

Overview As a member of the data engineering team, you will be the key technical expert developing and overseeing PepsiCo's data product build & operations and drive a strong vision for how data engineering can proactively create a positive impact on the business. You'll be an empowered member of a team of data engineers who build data pipelines into various source systems, rest data on the PepsiCo Data Lake, and enable exploration and access for analytics, visualization, machine learning, and product development efforts across the company. As a member of the data engineering team, you will help 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. You will work closely with process owners, product owners and business users. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. Responsibilities Be a founding member of the data engineering team. Help to attract talent to the team by networking with your peers, by representing PepsiCo HBS at conferences and other events, and by discussing our values and best practices when interviewing candidates. Own data pipeline development end-to-end, spanning data modeling, testing, scalability, operability and ongoing metrics. Ensure that we build high quality software by reviewing peer code check-ins. Define best practices for product development, engineering, and coding as part of a world class engineering team. Collaborate in architecture discussions and architectural decision making that is part of continually improving and expanding these platforms. Lead feature development in collaboration with other engineers; validate requirements / stories, assess current system capabilities, and decompose feature requirements into engineering tasks. Focus on delivering high quality data pipelines and tools through careful analysis of system capabilities and feature requests, peer reviews, test automation, and collaboration with other engineers. Develop software in short iterations to quickly add business value. Introduce new tools / practices to improve data and code quality; this includes researching / sourcing 3rd party tools and libraries, as well as developing tools in-house to improve workflow and quality for all data engineers. Support data pipelines developed by your teamthrough good exception handling, monitoring, and when needed by debugging production issues. Qualifications 6-9 years of overall technology experience that includes at least 5+ years of hands-on software development, data engineering, and systems architecture. 4+ years of experience in SQL optimization and performance tuning Experience with data modeling, data warehousing, and building high-volume ETL/ELT pipelines. Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets. Experience with data profiling and data quality tools like Apache Griffin, Deequ, or Great Expectations. Current skills in following technologies: Python Orchestration platforms: Airflow, Luigi, Databricks, or similar Relational databases: Postgres, MySQL, or equivalents MPP data systems: Snowflake, Redshift, Synapse, or similar Cloud platforms: AWS, Azure, or similar Version control (e.g., GitHub) and familiarity with deployment, CI/CD tools. Fluent with Agile processes and tools such as Jira or Pivotal Tracker Experience with running and scaling applications on the cloud infrastructure and containerized services like Kubernetes is a plus. Understanding of metadata management, data lineage, and data glossaries is a plus.

The Pega Senior Systems Architect (SSA) will be an integral member of our newly-formed Pega Delivery Team within the Trips Business Unit (TBU). The SSA will play a pivotal, hands-on role in the design, development, and implementation of robust Pega solutions tailored to meet our business objectives - reporting to an Engineering Manager. With 3-5 years of experience and requisite certification, the SSA will take on daily responsibilities to deliver high-quality technical Pega solutions for the TBU. They will work as part of an Engineering Team, adhering to Pega 'Best Practices' and established 'Ways of Working'. Candidates with recent experience in Pega 8.x and a thorough understanding of its architecture and design principles will be preferred. Familiarity with the Pega Customer Service Framework will be an added advantage. The SSA should be adept at navigating complex system requirements and translating them into efficient, scalable, and maintainable Pega applications. Their responsibilities will span the entire software development lifecycle, from initial requirement gathering to deployment and post-implementation support. Collaborating closely with both business stakeholders and the Pega Delivery Team, the SSA will ensure that crafted solutions align with enterprise standards while addressing specific business challenges. A dedication to best practices, continuous improvement, and mentoring junior team members is vital, as they will be regarded as a pillar of expertise and guidance within the team. They will be expected to guide, coach and mentor junior members in their team. In this dynamic role, the Pega SSA will also be tasked with staying updated on the latest Pega developments, innovations, and industry trends. Their proactive approach will catalyze the team's innovation, ensuring that our Pega solutions not only fulfill current demands but are also geared for future growth and adaptability. Join us in shaping the future of our Pega initiatives and fortifying our leadership in Pega solutions. Responsibility Maintain advanced knowledge of the Pega architecture and all Pega design and implementation practices. Maintain advanced knowledge about the latest features and tools provided by the Pega platform. Continuously enhance skill set and knowledge to leverage latest trends, techniques and practices and drive proactive change. Provide technical advice and guidance to team members while working with various (senior) stakeholders to solve complex problems and business requirements. Advocate for the adoption of a reusable components strategy in terms of enterprise solutions seeking to determine and develop repeatable, efficient and optimal ways of implementing Pega. Act as a mentor to the more junior SA team members, influencing them in design and developing best practices. Mentor and monitor the practices applied and quality of team deliverables. Can demonstrate innate troubleshooting skills when faced with complex problems, working systematically to resolve critical incidents in collaboration with the team in a timely fashion. Understand, value and consistently provide timely, specific and constructive feedback to team members and stakeholders regarding Pega practices and solutions. Enable the growth of Pega Citizen Development by providing internal training, upskilling and guidance. Lead simplistic designs that leverage OotB components and low-code options. Work with the internal Pega PGC (a COE function) to constantly define and refine Pega best practices and provide leadership to the team in the adoption of prescriptive development processes. Consistently design optimal solutions without unnecessary complexity and define a service oriented architecture. Work closely with the Product team and provide feedback regarding product enhancements needed to support the BUs or organizations needs. Work closely with the internal IT, Engineering and Architecture teams to understand hardware requirements, network landscape, server topologyand integration needs. Demonstrate leadership ability to back decisions with research and influence stakeholders accordingly. Demonstrate mindfulness of when to integrate with other products versus using Pega E2E and present the best architecture to meet desired needs. Years of relevant Job Knowledge Requirements of special knowledge/skills Expert knowledge of Pegasystems and Pega Customer Service apps in particular. In possession of valid Pega Lead System Architect certification. Degree in Computer Science, Information Technology or related field. Expertise in all phases of software development. Expertise in application servers,programming languages,relational and non-relational databases and integration techniques. Experience in Agile and Scrum methodologies. Extensive experience in coaching and mentoring more junior team members. Possesses a natural way of influencing stakeholders. Independent, good sense of responsibilities and goals. Excellent communication skills, able to influence and develop strong relationships. Ability to simplify complex problems.

What PepsiCo Data Management and Operations does: Maintain a predictable, transparent, global operating rhythm that ensures always-on access to high-quality data for stakeholders across the company Responsible for day-to-day data collection, transportation, maintenance/curation and access to the PepsiCo corporate data asset Work cross-functionally across the enterprise to centralize data and standardize it for use by business, data science or other stakeholders Increase awareness about available data and democratize access to it across the company As a member of the data engineering team, you will be the key technical expert developing and overseeing PepsiCo's data product build & operations and drive a strong vision for how data engineering can proactively create a positive impact on the business. You'll be an empowered member of a team of data engineers who build data pipelines into various source systems, rest data on the PepsiCo Data Lake, and enable exploration and access for analytics, visualization, machine learning, and product development efforts across the company. As a member of the data engineering team, you will help 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 . You will work closely with process owners, product owners and business users. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. Responsibilities Active contributor to code development in projects and services. 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. Develop and optimize procedures to productionalize data science models. Define and manage SLAs 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. Qualifications 8+ years of overall technology experience that includes at least 3+ years of hands-on software development, data engineering, and systems architecture. 3+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 3+ years of experience in SQL optimization and performance tuning, and development experience in programming languages like Python, PySpark, Scala etc.). 2+ years in cloud data engineering experience in Azure. Fluent with Azure cloud services. Azure Certification is a plus. 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 Azure Data Factory, Azure Databricks and Azure Machine learning tools is a plus. 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). BE/B Tech in Computer Science, Math, Physics, or other technical fields. Skills, Abilities, Knowledge: Excellent communication skills, both verbal and written, along with the ability to influence and demonstrate confidence in communications with senior level management. Proven track record of leading, mentoring data teams. Strong change manager. Comfortable with change, especially that which arises through company growth. Able to lead a team effectively through times of change. Ability to understand and translate business requirements into data and technical requirements. High degree of organization and ability to manage multiple, competing projects and priorities simultaneously. Positive and flexible attitude to enable adjusting to different needs in an ever-changing environment. Strong leadership, organizational and interpersonal skills; comfortable managing trade-offs. Foster a team culture of accountability, communication, and self-management. Proactively drives impact and engagement while bringing others along. Consistently attain/exceed individual and team goals Ability to lead others without direct authority in a matrixed environment. Differentiating Competencies Required Highly influential and having the ability to educate challenging stakeholders on the role of data and its purpose in the business. Understands both the engineering and business side of theData Productsreleased. Places the user in the center of decision making. Teams up and collaborates for speed, agility, and innovation. Experience with and embraces agile methodologies. Strong negotiation and decision-making skill. Experience managing and working with globally distributed teams.

Overview As Senior Analyst, Data Modeling, your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analyzing project data needs, identifying data storage and integration needs/issues, and driving opportunities for data model reuse, satisfying project requirements. Role will advocate Enterprise Architecture, Data Design, and D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architects teams. As a member of the data modeling team, you will create data models for very large and complex data applications in 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. The primary responsibilities of this role are to work with data product owners, data management owners, and data engineering teams to create physical and logical data models with an extensible philosophy to support future, unknown use cases with minimal rework. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. You will establish data design patterns that will drive flexible, scalable, and efficient data models to maximize value and reuse. Responsibilities Complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, EMR, Spark, DataBricks, Snowflake, Azure Synapse or other Cloud data warehousing technologies. Governs data design/modeling documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned. Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting. Supports assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices, and tools. Contributes to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development. Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework. Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives, maximizes reuse. Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper management: business and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations. Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development. Assist with data planning, sourcing, collection, profiling, and transformation. Create Source To Target Mappings for ETL and BI developers. Show expertise for data at all levels: low-latency, relational, and unstructured data stores; analytical and data lakes; data str/cleansing. Partner with the Data Governance team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders. Support data lineage and mapping of source system data to canonical data stores for research, analysis and productization. Qualifications 8+ years of overall technology experience that includes at least 4+ years of data modeling and systems architecture. 3+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 4+ years of experience developing enterprise data models. Experience in building solutions in the retail or in the supply chain space. Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models). Experience with integration of multi cloud services (Azure) with on-premises technologies. 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, Teradata or SnowFlake. Experience with version control systems like Github and deployment & CI tools. Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus. Experience 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).

What PepsiCo Data Management and Operations does: Maintain a predictable, transparent, global operating rhythm that ensures always-on access to high-quality data for stakeholders across the company. Responsible for day-to-day data collection, transportation, maintenance/curation, and access to the PepsiCo corporate data asset. Senior Data Engineer: As a Sr.data engineering, you will be the key technical expert overseeing PepsiCo's data product build & operations and drive a strong vision for how data engineering can proactively create a positive impact on the business. You'll be empowered to create & lead a strong team of data engineers who build data pipelines into various source systems, rest data on the PepsiCo Data Lake, and enable exploration and access for analytics, visualization, machine learning, and product development efforts across the company. As a member of the data engineering team, you will help 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. You will work closely with process owners, product owners and business users. You'll be working in a hybrid environment with in-house, on-premises data sources as well as cloud and remote systems. Ideally Candidate must be flexible to work an alternative schedule either on tradition work week from Monday to Friday; or Tuesday to Saturday or Sunday to Thursday depending upon coverage requirements of the job. The candidate can work with immediate supervisor to change the work schedule on rotational basis depending on the product and project requirements. Responsibilities Create reusable accelerators and solutions to migrate data from legacy data warehouse platforms such as Teradata to Azure Databricks Enable and accelerate standards-based development prioritizing reuse of code, adopt test-driven development, unit testing and test automation with end-to-end observability of data Build and own the automation and monitoring frameworks that captures metrics and operational KPIs for data pipeline quality, performance and cost. Responsible for implementing best practices around systems integration, security, performance, and data management. Collaborate with internal clients (product teams, sector leads, data science) and external partners (SI partners/data providers) to drive solutioning and clarify solution requirements. Overseework with internal clients and external partners to Evolve the architectural capabilities and maturity of the data platform by engaging with enterprise architects to build and support the right domain architecture for each application following well-architected design standards. Define and manage SLAs for data products and processes running in production. Support large-scale experimentation done by data scientists. Prototype new approaches and build solutions at scale. Create documentation for learnings and knowledge transfer to internal associates. Qualifications 9+ years of overall technology experience that includes at least 4+ years of hands-on software development, data engineering, and systems architecture. 3+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 3+ years of experience in SQL optimization and performance tuning on MS SQL Server, Azure SQL or any other popular RDBMS 3+ years of experience in Python and Pyspark/Scala programming on big data platforms like Databricks 3+ years in cloud data engineering experience in Azure or AWS. Fluent with Azure cloud services. Azure Data Engineering certification is a plus. Experience with integration of multi cloud services with on-premises technologies. Domain Knowledge in CPG industry with Supply chain/GTM background is preferred. Experience with data modelling, data warehousing, and building high-volume ETL/ELT pipelines. Experience with data profiling and data quality tools like 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 Databricks, 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 ADO, Github and CI/CD tools for deployment. Experience with Azure Data Factory, Azure Databricks and Azure Machine learning 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. Familiarity with business intelligence tools (such as PowerBI). BA/BS in Computer Science, Math, Physics, or other technical fields. Candidate must be flexible to work an alternative work schedule either on tradition work week from Monday to Friday; or Tuesday to Saturday or Sunday to Thursday depending upon product and project coverage requirements of the job. Candidates are expected to be in the office at the assigned location at least 3 days a week and the days at work needs to be coordinated with immediate supervisor

Role Purpose The purpose of the role is to create exceptional architectural solution design and thought leadership and enable delivery teams to provide exceptional client engagement and satisfaction. Do 1.Develop architectural solutions for the new deals/ major change requests in existing deals Creates an enterprise-wide architecture that ensures systems are scalable, reliable, and manageable. Provide solutioning of RFP's received from clients and ensure overall design assurance Develop a direction to manage the portfolio of to-be-solutions including systems, shared infrastructure services, applications in order to better match business outcome objectives Analyse technology environment, enterprise specifics, client requirements to set a collaboration solution design framework/ architecture Provide technical leadership to the design, development and implementation of custom solutions through thoughtful use of modern technology Define and understand current state solutions and identify improvements, options & tradeoffs to define target state solutions Clearly articulate, document and sell architectural targets, recommendations and reusable patterns and accordingly propose investment roadmaps Evaluate and recommend solutions to integrate with overall technology ecosystem Works closely with various IT groups to transition tasks, ensure performance and manage issues through to resolution Perform detailed documentation (App view, multiple sections & views) of the architectural design and solution mentioning all the artefacts in detail Validate the solution/ prototype from technology, cost structure and customer differentiation point of view Identify problem areas and perform root cause analysis of architectural design and solutions and provide relevant solutions to the problem Collaborating with sales, program/project, consulting teams to reconcile solutions to architecture Tracks industry and application trends and relates these to planning current and future IT needs Provides technical and strategic input during the project planning phase in the form of technical architectural designs and recommendation Collaborates with all relevant parties in order to review the objectives and constraints of solutions and determine conformance with the Enterprise Architecture Identifies implementation risks and potential impacts 2.Enable Delivery Teams by providing optimal delivery solutions/ frameworks Build and maintain relationships with executives, technical leaders, product owners, peer architects and other stakeholders to become a trusted advisor Develops and establishes relevant technical, business process and overall support metrics (KPI/SLA) to drive results Manages multiple projects and accurately reports the status of all major assignments while adhering to all project management standards Identify technical, process, structural risks and prepare a risk mitigation plan for all the projects Ensure quality assurance of all the architecture or design decisions and provides technical mitigation support to the delivery teams Recommend tools for reuse, automation for improved productivity and reduced cycle times Leads the development and maintenance of enterprise framework and related artefacts Develops trust and builds effective working relationships through respectful, collaborative engagement across individual product teams Ensures architecture principles and standards are consistently applied to all the projects Ensure optimal Client Engagement Support pre-sales team while presenting the entire solution design and its principles to the client Negotiate, manage and coordinate with the client teams to ensure all requirements are met and create an impact of solution proposed Demonstrate thought leadership with strong technical capability in front of the client to win the confidence and act as a trusted advisor 3.Competency Building and Branding Ensure completion of necessary trainings and certifications Develop Proof of Concepts (POCs),case studies, demos etc. for new growth areas based on market and customer research Develop and present a point of view of Wipro on solution design and architect by writing white papers, blogs etc. Attain market referencability and recognition through highest analyst rankings, client testimonials and partner credits Be the voice of Wipro's Thought Leadership by speaking in forums (internal and external) Mentor developers, designers and Junior architects in the project for their further career development and enhancement Contribute to the architecture practice by conducting selection interviews etc 4.Team Management Resourcing Anticipating new talent requirements as per the market/ industry trends or client requirements Hire adequate and right resources for the team Talent Management Ensure adequate onboarding and training for the team members to enhance capability & effectiveness Build an internal talent pool and ensure their career progression within the organization Manage team attrition Drive diversity in leadership positions Performance Management Set goals for the team, conduct timely performance reviews and provide constructive feedback to own direct reports Ensure that the Performance Nxt is followed for the entire team Employee Satisfaction and Engagement Lead and drive engagement initiatives for the team Track team satisfaction scores and identify initiatives to build engagement within the team

Overview Working with bothNorth America Sector business, S&T partners and Enterprise Architects, this role will lead the NA effort to identify gaps and help design interfaces to bring data from various sources. Design and architect robust solutions, evaluate existing components and systems to determine integration requirements. Integration team leadership; mentoring, coaching, and educating team on best practices in integration design and development. Manage the integration, analysis and assessment of plans and strategies across multiple projects. Ensure that the final solutions meet project and organizational needs.Provide oversight in standards adherence through reviews of detailed technical specifications. Work with gIBP team to understand requirements for integration strategies and patterns are adhering to Enterprise Architects approved standards. Responsibilities Knowledge of enterprise architecture, systems architecture, integration architecture and data architecture standards, frameworks, and practices Good understanding of data model and mapping. Experience with the implementation of CI/CD practices Proven experience in managing relationships with IT teams and internal stakeholders. Prepare or review product documentation, technical design document for accuracy and completeness. Debug and tune data integration processes, exception data processing, troubleshoot and recommend improvements and alternate methodologies. Demonstrated experience with data integration architectures, data analysis and implementation of Integration solutions. Qualifications Qualifications 10+ years of IT experience 7+ years of experience in Middleware and Integration. Ability to work effectively with both business and technical stakeholders Ability to communicate and work with global IBP IT and business partners Excellent communication skills, strong analytical, problem-solving, and interpersonal skills. Experience in a high-paced environment, with the ability to build positive working relationships

The Pega Senior Systems Architect (SSA) will be an integral member of our newly-formed Pega Delivery Team within the Trips Business Unit (TBU). The SSA will play a pivotal, hands-on role in the design, development, and implementation of robust Pega solutions tailored to meet our business objectives - reporting to an Engineering Manager. With 3-5 years of experience and requisite certification, the SSA will take on daily responsibilities to deliver high-quality technical Pega solutions for the TBU. They will work as part of an Engineering Team, adhering to Pega 'Best Practices' and established 'Ways of Working'. Candidates with recent experience in Pega 8.x and a thorough understanding of its architecture and design principles will be preferred. Familiarity with the Pega Customer Service Framework will be an added advantage. The SSA should be adept at navigating complex system requirements and translating them into efficient, scalable, and maintainable Pega applications. Their responsibilities will span the entire software development lifecycle, from initial requirement gathering to deployment and post-implementation support. Collaborating closely with both business stakeholders and the Pega Delivery Team, the SSA will ensure that crafted solutions align with enterprise standards while addressing specific business challenges. A dedication to best practices, continuous improvement, and mentoring junior team members is vital, as they will be regarded as a pillar of expertise and guidance within the team. They will be expected to guide, coach and mentor junior members in their team. In this dynamic role, the Pega SSA will also be tasked with staying updated on the latest Pega developments, innovations, and industry trends. Their proactive approach will catalyze the team's innovation, ensuring that our Pega solutions not only fulfill current demands but are also geared for future growth and adaptability. Join us in shaping the future of our Pega initiatives and fortifying our leadership in Pega solutions. Responsibility Maintain advanced knowledge of the Pega architecture and all Pega design and implementation practices. Maintain advanced knowledge about the latest features and tools provided by the Pega platform. Continuously enhance skill set and knowledge to leverage latest trends, techniques and practices and drive proactive change. Provide technical advice and guidance to team members while working with various (senior) stakeholders to solve complex problems and business requirements. Advocate for the adoption of a reusable components strategy in terms of enterprise solutions seeking to determine and develop repeatable, efficient and optimal ways of implementing Pega. Act as a mentor to the more junior SA team members, influencing them in design and developing best practices. Mentor and monitor the practices applied and quality of team deliverables. Can demonstrate innate troubleshooting skills when faced with complex problems, working systematically to resolve critical incidents in collaboration with the team in a timely fashion. Understand, value and consistently provide timely, specific and constructive feedback to team members and stakeholders regarding Pega practices and solutions. Enable the growth of Pega Citizen Development by providing internal training, upskilling and guidance. Lead simplistic designs that leverage OotB components and low-code options. Work with the internal Pega PGC (a COE function) to constantly define and refine Pega best practices and provide leadership to the team in the adoption of prescriptive development processes. Consistently design optimal solutions without unnecessary complexity and define a service oriented architecture. Work closely with the Product team and provide feedback regarding product enhancements needed to support the BUs or organizations needs. Work closely with the internal IT, Engineering and Architecture teams to understand hardware requirements, network landscape, server topologyand integration needs. Demonstrate leadership ability to back decisions with research and influence stakeholders accordingly. Demonstrate mindfulness of when to integrate with other products versus using Pega E2E and present the best architecture to meet desired needs. Years of relevant Job Knowledge Requirements of special knowledge/skills Expert knowledge of Pegasystems and Pega Customer Service apps in particular. In possession of valid Pega Lead System Architect certification. Degree in Computer Science, Information Technology or related field. Expertise in all phases of software development. Expertise in application servers,programming languages,relational and non-relational databases and integration techniques. Experience in Agile and Scrum methodologies. Extensive experience in coaching and mentoring more junior team members. Possesses a natural way of influencing stakeholders. Independent, good sense of responsibilities and goals. Excellent communication skills, able to influence and develop strong relationships. Ability to simplify complex problems.

What PepsiCo Data Management and Operations does: Maintain a predictable, transparent, global operating rhythm that ensures always-on access to high-quality data for stakeholders across the company. Responsible for day-to-day data collection, transportation, maintenance/curation, and access to the PepsiCo corporate data asset Work cross-functionally across the enterprise to centralize data and standardize it for use by business, data science or other stakeholders. Increase awareness about available data and democratize access to it across the company. As a Data Engineering Associate Manager, you will be the key technical expert overseeing PepsiCo's data product build & operations and drive a strong vision for how data engineering can proactively create a positive impact on the business. You'll be empowered to create & lead a strong team of data engineers who build data pipelines into various source systems, rest data on the PepsiCo Data Lake, and enable exploration and access for analytics, visualization, machine learning, and product development efforts across the company. As a member of the data engineering team, you will help 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. You will work closely with process owners, product owners and business users. You'll be working in a hybrid environment with in-house, on-premises data sources as well as cloud and remote systems. Responsibilities Provide leadership and management to a team of data engineers, 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. Overseework 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 SLAs 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. Qualifications B.Tech in Computer Science, Math, Physics, or other technical fields. 11+ years of overall technology experience that includes at least 5+ years of hands-on software development, data engineering, and systems architecture. 4+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 4+ years of experience in SQL optimization and performance tuning, and development experience in programming languages like Python, PySpark, Scala etc.). 2+ years in cloud data engineering experience in Azure. Fluent with Azure cloud services. Azure Certification is a plus. Experience in Azure Log Analytics Experience with integration of multi cloud services with on-premises technologies. Experience with data modelling, 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 Azure Data Factory, Azure Databricks and Azure Machine learning 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).

Overview Deputy Director - Data Engineering PepsiCo operates in an environment undergoing immense and rapid change. Big-data and digital technologies are driving business transformation that is unlocking new capabilities and business innovations in areas like eCommerce, mobile experiences and IoT. The key to winning in these areas is being able to leverage enterprise data foundations built on PepsiCos global business scale to enable business insights, advanced analytics, and new product development. PepsiCos Data Management and Operations team is tasked with the responsibility of developing quality data collection processes, maintaining the integrity of our data foundations, and enabling business leaders and data scientists across the company to have rapid access to the data they need for decision-making and innovation. What PepsiCo Data Management and Operations does: Maintain a predictable, transparent, global operating rhythm that ensures always-on access to high-quality data for stakeholders across the company. Responsible for day-to-day data collection, transportation, maintenance/curation, and access to the PepsiCo corporate data asset Work cross-functionally across the enterprise to centralize data and standardize it for use by business, data science or other stakeholders. Increase awareness about available data and democratize access to it across the company. As a data engineering lead, you will be the key technical expert overseeing PepsiCo's data product build & operations and drive a strong vision for how data engineering can proactively create a positive impact on the business. You'll be empowered to create & lead a strong team of data engineers who build data pipelines into various source systems, rest data on the PepsiCo Data Lake, and enable exploration and access for analytics, visualization, machine learning, and product development efforts across the company. As a member of the data engineering team, you will help 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. You will work closely with process owners, product owners and business users. You'll be working in a hybrid environment with in-house, on-premises data sources as well as cloud and remote systems. Responsibilities Data engineering lead role for D&Ai data modernization (MDIP) Ideally Candidate must be flexible to work an alternative schedule either on tradition work week from Monday to Friday; or Tuesday to Saturday or Sunday to Thursday depending upon coverage requirements of the job. The can didate can work with immediate supervisor to change the work schedule on rotational basis depending on the product and project requirements. Responsibilities Manage a team of data engineers and data analysts by delegating project responsibilities and managing their flow of work as well as empowering them to realize their full potential. Design, structure and store data into unified data models and link them together to make the data reusable for downstream products. Manage and scale data pipelines from internal and external data sources to support new product launches and drive data quality across data products. Create reusable accelerators and solutions to migrate data from legacy data warehouse platforms such as Teradata to Azure Databricks and Azure SQL. Enable and accelerate standards-based development prioritizing reuse of code, adopt test-driven development, unit testing and test automation with end-to-end observability of data Build and own the automation and monitoring frameworks that captures metrics and operational KPIs for data pipeline quality, performance and cost. Collaborate with internal clients (product teams, sector leads, data science teams) and external partners (SI partners/data providers) to drive solutioning and clarify solution requirements. Evolve the architectural capabilities and maturity of the data platform by engaging with enterprise architects to build and support the right domain architecture for each application following well-architected design standards. Define and manage SLAs for data products and processes running in production. Create documentation for learnings and knowledge transfer to internal associates. Qualifications 12+ years of engineering and data management experience Qualifications 12+ years of overall technology experience that includes at least 5+ years of hands-on software development, data engineering, and systems architecture. 8+ years of experience with Data Lakehouse, Data Warehousing, and Data Analytics tools. 6+ years of experience in SQL optimization and performance tuning on MS SQL Server, Azure SQL or any other popular RDBMS 6+ years of experience in Python/Pyspark/Scala programming on big data platforms like Databricks 4+ years in cloud data engineering experience in Azure or AWS. Fluent with Azure cloud services. Azure Data Engineering certification is a plus. Experience with integration of multi cloud services with on-premises technologies. Experience with data modelling, data warehousing, and building high-volume ETL/ELT pipelines. Experience with data profiling and data quality tools like Great Expectations. Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets. Experience with at least one business intelligence tool such as Power BI or Tableau Experience with running and scaling applications on the cloud infrastructure and containerized services like Kubernetes. Experience with version control systems like ADO, Github and CI/CD tools for DevOps automation and deployments. Experience with Azure Data Factory, Azure Databricks and Azure Machine learning 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. BA/BS in Computer Science, Math, Physics, or other technical fields. Candidate must be flexible to work an alternative work schedule either on tradition work week from Monday to Friday; or Tuesday to Saturday or Sunday to Thursday depending upon product and project coverage requirements of the job. Candidates are expected to be in the office at the assigned location at least 3 days a week and the days at work needs to be coordinated with immediate supervisor Skills, Abilities, Knowledge: Excellent communication skills, both verbal and written, along with the ability to influence and demonstrate confidence in communications with senior level management. Proven track record of leading, mentoring data teams. Strong change manager. Comfortable with change, especially that which arises through company growth. Ability to understand and translate business requirements into data and technical requirements. High degree of organization and ability to manage multiple, competing projects and priorities simultaneously. Positive and flexible attitude to enable adjusting to different needs in an ever-changing environment. Strong leadership, organizational and interpersonal skills; comfortable managing trade-offs. Foster a team culture of accountability, communication, and self-management. Proactively drives impact and engagement while bringing others along. Consistently attain/exceed individual and team goals. Ability to lead others without direct authority in a matrixed environment. Comfortable working in a hybrid environment with teams consisting of contractors as well as FTEs spread across multiple PepsiCo locations. Domain Knowledge in CPG industry with Supply chain/GTM background is preferred.