518 Data Munging Jobs - Page 2

Project Role : Software Development Engineer Project Role Description : Analyze, design, code and test multiple components of application code across one or more clients. Perform maintenance, enhancements and/or development work. Must have skills : SAS BI Good to have skills : NAMinimum 2 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Software Development Engineer, you will analyze, design, code, and test multiple components of application code across one or more clients. You will perform maintenance, enhancements, and/or development work, contributing to the overall success of the projects. Roles & Responsibilities:- Expected to perform independently and become an SME.- Required active participation/contribution in team discussions.- Contribute in providing solutions to work-related problems.- Collaborate with team members to analyze, design, and develop software solutions.- Participate in code reviews and provide constructive feedback.- Troubleshoot and debug software applications to ensure optimal performance.- Document software specifications and ensure code quality.- Stay updated with industry trends and technologies to enhance skills. Professional & Technical Skills: - Must To Have Skills: Proficiency in SAS BI.- Strong understanding of statistical analysis and machine learning algorithms.- Experience with data visualization tools such as Tableau or Power BI.- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms.- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information:- The candidate should have a minimum of 2 years of experience in SAS BI.- This position is based at our Chennai office.- A 15 years full-time education is required. Qualification 15 years full time education

Project Role : Application Lead Project Role Description : Lead the effort to design, build and configure applications, acting as the primary point of contact. Must have skills : PySpark Good to have skills : NAMinimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an Application Lead, you will lead the effort to design, build, and configure applications, acting as the primary point of contact. You will be responsible for overseeing the entire application development process and ensuring its successful implementation. Your role will involve collaborating with cross-functional teams, managing the team's performance, and making key decisions. You will also provide solutions to problems for your immediate team and across multiple teams, contributing to the overall success of the project. Roles & Responsibilities:- Expected to be an SME- Collaborate and manage the team to perform- Responsible for team decisions- Engage with multiple teams and contribute to key decisions- Provide solutions to problems for their immediate team and across multiple teams- Lead the effort to design, build, and configure applications- Act as the primary point of contact for application-related matters- Oversee the entire application development process- Ensure successful implementation of applications Professional & Technical Skills: - Must To Have Skills: Proficiency in PySpark- Strong understanding of statistical analysis and machine learning algorithms- Experience with data visualization tools such as Tableau or Power BI- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity Additional Information:- The candidate should have a minimum of 5 years of experience in PySpark- This position is based in Gurugram- A 15 years full-time education is required Qualification 15 years full time education

Overview Enterprise Data Operations Analyst Job OverviewAs an 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 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 managementbusiness 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 levelslow-latency, relational, and unstructured data stores; analytical and data lakes; data streaming (consumption/production), data in-transit. Develop reusable data models based on cloud-centric, code-first approaches to data management and 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 Qualifications 5+ years of overall technology experience that includes at least 2+ years of data modeling and systems architecture. Around 2+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 2+ 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 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 managementbusiness 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 levelslow-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 Platform engineering team, you will be the key techno functional expert leading and overseeing PepsiCo's Platforms & operations and drive a strong vision for how Platforms engineering can proactively create a positive impact on the business. You'll be an empowered Leader of a team of Platform engineers who build Platform products for platform optimization and cost optimization and build tools for Platform ops and Data Ops on the PepsiCo Data Lake, and enable exploration and access for analytics, visualization, machine learning, and product development efforts across the company. As Leader of the Platform engineering team, you will help in managing platform Governance team that builds frameworks to guardrail the platforms of very large and complex data applications in public cloud environments and directly impact 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 Active contributor to cost optimization of platforms and services. Manage and scale Azure Data Platforms to support new product launches and drive Platform Stability and Observability across data products. Build and own the automation and monitoring frameworks that captures metrics and operational KPIs for Data Platforms for cost and performance. Responsible for implementing best practices around systems integration, security, performance and Platform 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 production Alize data science models. Define and manage SLAs for Platforms 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 10+ years of overall technology experience that includes at least 4+ years of hands-on software development, Program management, and Advanced Analytics. 4+ years of experience with Power BI, Tableau, Data Warehousing, and Data Analytics tools. 4+ years of experience in Platform optimization and performance tuning Experience in managing multiple teams and coordinating with different stakeholders to implement the vision of the team. 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 Symantec Models. Proficient in DAX queries, Copilot and AI Skills Experience building/operating highly available, distributed systems of data Visualization . Experience with at least one MPP database technology such as Redshift, Synapse or Snowflake. Experience with version control systems like Github and deployment & CI tools. Knowledge of Azure Data Factory, Azure Databricks. 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 Augmented Analytics tools is Plus (such as ThoughtSpot, Tellius).

Overview As an 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 managementbusiness 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 levelslow-latency, relational, and unstructured data stores; analytical and data lakes; data streaming (consumption/production), data in-transit. Develop reusable data models based on cloud-centric, code-first approaches to data management and 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 4+ years of overall technology experience that includes at least 2+ years of data modeling and systems architecture. Around 2+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 2+ 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 Enterprise Data Operations Sr Analyst L08 Job OverviewAs 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 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 managementbusiness 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 levelslow-latency, relational, and unstructured data stores; analytical and data lakes; data streaming (consumption/production), data in-transit. Develop reusable data models based on cloud-centric, code-first approaches to data management and 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 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 ). Does the person hired for this job need to be based in a PepsiCo office, or can they be remote Employee must be based in a Pepsico office Primary Work LocationHyderabad HUB-IND

Overview 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. 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. 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 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 8+ years of overall technology experience that includes at least 4+ 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). 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.

Overview 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. 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 enginee r , you will be the key technical expert building PepsiCo's data product s to drive a strong vision. You'll be empowered to create 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 developing 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 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 4 + 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 in Azure Log Analytics

Overview As an 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 managementbusiness 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 levelslow-latency, relational, and unstructured data stores; analytical and data lakes; data streaming (consumption/production), data in-transit. Develop reusable data models based on cloud-centric, code-first approaches to data management and 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 5+ years of overall technology experience that includes at least 2+ years of data modeling and systems architecture. Around 2+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 2+ 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 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. 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 6+ years of overall technology experience that includes at least 4+ 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 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. 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). BA/BS in Computer Science, Math, Physics, or other technical fields.

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 managementbusiness 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 levelslow-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).

About The Role Project Role : Application Lead Project Role Description : Lead the effort to design, build and configure applications, acting as the primary point of contact. Must have skills : MicroStrategy Business Intelligence, Microsoft Power Business Intelligence (BI) Good to have skills : NAMinimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an Application Lead, you will lead the effort to design, build, and configure applications, acting as the primary point of contact. You will be responsible for managing the team and ensuring successful project delivery. Your typical day will involve collaborating with multiple teams, making key decisions, and providing solutions to problems for your immediate team and across multiple teams. Roles & Responsibilities:- Expected to be an SME- Collaborate and manage the team to perform- Responsible for team decisions- Engage with multiple teams and contribute on key decisions- Provide solutions to problems for their immediate team and across multiple teams- Lead the effort to design, build, and configure applications- Act as the primary point of contact for the project- Manage the team and ensure successful project delivery- Collaborate with multiple teams to make key decisions- Provide solutions to problems for the immediate team and across multiple teams Professional & Technical Skills: - Must To Have Skills: Proficiency in MicroStrategy Business Intelligence, Microsoft Power Business Intelligence (BI)- Strong understanding of statistical analysis and machine learning algorithms- Experience with data visualization tools such as Tableau or Power BI- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity Additional Information:- The candidate should have a minimum of 5 years of experience in MicroStrategy Business Intelligence- This position is based at our Indore office- A 15 years full-time education is required Qualification 15 years full time education

About The Role Project Role : Data Platform Engineer Project Role Description : Assists with the data platform blueprint and design, encompassing the relevant data platform components. Collaborates with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models. Must have skills : PySpark Good to have skills : Python (Programming Language)Minimum 3 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Data Platform Engineer, you will assist with the data platform blueprint and design, collaborating with Integration Architects and Data Architects to ensure cohesive integration between systems and data models. You will play a crucial role in shaping the data platform components. Roles & Responsibilities:- Expected to perform independently and become an SME.- Required active participation/contribution in team discussions.- Contribute in providing solutions to work related problems.- Assist with the data platform blueprint and design.- Collaborate with Integration Architects and Data Architects.- Ensure cohesive integration between systems and data models.- Implement data platform components effectively.- Provide insights for enhancing data platform performance. Professional & Technical Skills: - Must To Have Skills: Proficiency in PySpark.- Strong understanding of statistical analysis and machine learning algorithms.- Experience with data visualization tools such as Tableau or Power BI.- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms.- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information:- The candidate should have a minimum of 3 years of experience in PySpark.- This position is based at our Kolkata office.- A 15 years full time education is required. Qualification 15 years full time education

About The Role Project Role : Application Developer Project Role Description : Design, build and configure applications to meet business process and application requirements. Must have skills : Databricks Unified Data Analytics Platform Good to have skills : Apache Spark, PySparkMinimum 7.5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an Application Developer, you will design, build, and configure applications to meet business process and application requirements. You will be responsible for creating efficient and scalable applications that align with the organization's goals and objectives. Your typical day will involve collaborating with cross-functional teams, analyzing business requirements, designing application architecture, and implementing solutions to meet user needs. You will also be involved in troubleshooting and resolving application issues, as well as ensuring the security and integrity of the applications. Roles & Responsibilities:- Expected to be an SME, collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Provide solutions to problems for their immediate team and across multiple teams.- Design, build, and configure applications to meet business process and application requirements.- Analyze business requirements and translate them into technical specifications.- Collaborate with cross-functional teams to gather requirements and understand user needs.- Design application architecture and develop efficient and scalable solutions.- Implement and test application functionality and ensure its alignment with business objectives. Professional & Technical Skills: - Must To Have Skills: Proficiency in Databricks Unified Data Analytics Platform.- Good To Have Skills: Experience with Apache Spark, PySpark, Talend ETL.- Strong understanding of statistical analysis and machine learning algorithms.- Experience with data visualization tools such as Tableau or Power BI.- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms.- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information:- The candidate should have a minimum of 7.5 years of experience in Databricks Unified Data Analytics Platform.- This position is based at our Bengaluru office.- A 15 years full-time education is required. Qualification 15 years full time education

About The Role Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Large Language Models Good to have skills : NAMinimum 7.5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an AI/ML Engineer, you will develop applications and systems utilizing AI tools, Cloud AI services, and GenAI models. Your role involves implementing deep learning, neural networks, chatbots, and image processing in production-ready quality solutions. Roles & Responsibilities:- Expected to perform independently and become an SME.- Required active participation/contribution in team discussions.- Contribute in providing solutions to work-related problems.- Develop applications and systems using AI tools and Cloud AI services.- Implement deep learning and neural networks in solutions.- Create chatbots and work on image processing tasks.- Collaborate with team members to provide innovative solutions.- Stay updated with the latest AI/ML trends and technologies. Professional & Technical Skills: - Must To Have Skills: Proficiency in Large Language Models.- Strong understanding of statistical analysis and machine learning algorithms.- Experience with data visualization tools such as Tableau or Power BI.- Hands-on implementing various machine learning algorithms like linear regression, logistic regression, decision trees, and clustering algorithms.- Solid grasp of data munging techniques including data cleaning, transformation, and normalization. Additional Information:- The candidate should have a minimum of 3 years of experience in Large Language Models.- This position is based at our Bengaluru office.- A 15 years full-time education is required. Qualification 15 years full time education

About The Role Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Machine Learning Good to have skills : NAMinimum 3 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an AI/ML Engineer, you will develop applications and systems utilizing AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production-ready quality. You will apply GenAI models as part of the solution, including deep learning, neural networks, chatbots, and image processing. Roles & Responsibilities:- Expected to perform independently and become an SME.- Required active participation/contribution in team discussions.- Contribute in providing solutions to work-related problems.- Develop applications and systems utilizing AI tools and Cloud AI services.- Apply GenAI models as part of the solution.- Implement deep learning and neural networks.- Create chatbots and work on image processing.- Collaborate with the team to provide innovative solutions. Professional & Technical Skills: - Must To Have Skills: Proficiency in Machine Learning.- Strong understanding of statistical analysis and machine learning algorithms.- Experience with data visualization tools such as Tableau or Power BI.- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms.- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information:- The candidate should have a minimum of 3 years of experience in Machine Learning.- This position is based at our Hyderabad office.- A 15 years full-time education is required. Qualification 15 years full time education

About The Role Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Data Engineering Good to have skills : NAMinimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an AI/ML Engineer, you will develop applications and systems utilizing AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production-ready quality. You will apply GenAI models as part of the solution, including deep learning, neural networks, chatbots, and image processing. Roles & Responsibilities:- Expected to be an SME.- Collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Provide solutions to problems for their immediate team and across multiple teams.- Lead the implementation of AI/ML models.- Conduct research on emerging AI technologies.- Optimize AI algorithms for performance and scalability. Professional & Technical Skills: - Must To Have Skills: Proficiency in Data Engineering.- Strong understanding of statistical analysis and machine learning algorithms.- Experience with data visualization tools such as Tableau or Power BI.- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms.- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information:- The candidate should have a minimum of 5 years of experience in Data Engineering.- This position is based at our Bengaluru office.- A 15 years full-time education is required. Qualification 15 years full time education

About The Role Project Role : Data Platform Architect Project Role Description : Architects the data platform blueprint and implements the design, encompassing the relevant data platform components. Collaborates with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models. Must have skills : Databricks Unified Data Analytics Platform Good to have skills : NAMinimum 12 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an Application Developer, you will design, build, and configure applications to meet business process and application requirements. Your typical day will involve collaborating with the team to develop and implement solutions that align with the organization's goals and objectives. You will utilize your expertise in Databricks Unified Data Analytics Platform to create efficient and effective applications that enhance business processes and drive innovation. Roles & Responsibilities:- Expected to be an SME, collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Expected to provide solutions to problems that apply across multiple teams.- Collaborate with stakeholders to gather requirements and understand business needs.- Design and develop applications using Databricks Unified Data Analytics Platform.- Configure and customize applications to meet specific business process requirements.- Perform code reviews and ensure adherence to coding standards.- Provide technical guidance and mentorship to junior team members. Professional & Technical Skills: - Must To Have Skills: Proficiency in Databricks Unified Data Analytics Platform.- Good To Have Skills: Experience with Microsoft Azure Data Services, Microsoft Azure Analytics Services.- Strong understanding of statistical analysis and machine learning algorithms.- Experience with data visualization tools such as Tableau or Power BI.- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms.- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information:- The candidate should have a minimum of 12 years of experience in Databricks Unified Data Analytics Platform.- This position is based at our Chennai office.- A Full Time Education is required. Qualification 15 years full time education

About The Role Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Large Language Models Good to have skills : NAMinimum 12 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an AI / ML Engineer, you will develop applications and systems utilizing AI tools, Cloud AI services, and GenAI models. Your role involves creating cloud or on-prem application pipelines with production-ready quality, incorporating deep learning, neural networks, chatbots, and image processing. Roles & Responsibilities:- Expected to be an SME.- Collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Expected to provide solutions to problems that apply across multiple teams.- Lead research and development initiatives in AI and ML technologies.- Implement and optimize machine learning models.- Conduct data analysis and interpretation for business insights. Professional & Technical Skills: - Must To Have Skills: Proficiency in Large Language Models.- Strong understanding of statistical analysis and machine learning algorithms.- Experience with data visualization tools such as Tableau or Power BI.- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms.- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information:- The candidate should have a minimum of 12 years of experience in Large Language Models.- This position is based at our Bengaluru office.- A 15 years full-time education is required. Qualification 15 years full time education

About The Role Project Role : Application Developer Project Role Description : Design, build and configure applications to meet business process and application requirements. Must have skills : Databricks Unified Data Analytics Platform Good to have skills : NAMinimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an Application Developer, you will design, build, and configure applications to meet business process and application requirements. You will collaborate with teams, make team decisions, and provide solutions to problems. Your typical day will involve designing and developing applications, collaborating with multiple teams, and contributing to key decisions. Roles & Responsibilities:- Expected to be an SME- Collaborate and manage the team to perform- Responsible for team decisions- Engage with multiple teams and contribute on key decisions- Provide solutions to problems for their immediate team and across multiple teams- Design and develop applications- Collaborate with cross-functional teams- Contribute to key decisions Professional & Technical Skills: - Must To Have Skills: Proficiency in Databricks Unified Data Analytics Platform- Strong understanding of statistical analysis and machine learning algorithms- Experience with data visualization tools such as Tableau or Power BI- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity Additional Information:- The candidate should have a minimum of 5 years of experience in Databricks Unified Data Analytics Platform- This position is based at our Bengaluru office- A 15 years full time education is required Qualification 15 years full time education

About The Role Project Role : Application Lead Project Role Description : Lead the effort to design, build and configure applications, acting as the primary point of contact. Must have skills : PySpark Good to have skills : NAMinimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an Application Lead, you will lead the effort to design, build, and configure applications, acting as the primary point of contact. You will be responsible for overseeing the entire application development process and ensuring its successful implementation. Roles & Responsibilities:- Expected to perform independently and become an SME.- Required active participation/contribution in team discussions.- Contribute in providing solutions to work-related problems.- Lead the design, development, and implementation of applications.- Collaborate with cross-functional teams to gather and analyze requirements.- Ensure the applications meet quality standards and are delivered on time.- Provide technical guidance and mentorship to junior team members.- Stay updated with the latest industry trends and technologies.- Identify and resolve any issues or bottlenecks in the application development process. Professional & Technical Skills: - Must To Have Skills: Proficiency in PySpark.- Strong understanding of statistical analysis and machine learning algorithms.- Experience with data visualization tools such as Tableau or Power BI.- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms.- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information:- The candidate should have a minimum of 2 years of experience in PySpark.- This position is based at our Hyderabad office.- A 15 years full-time education is required. Qualification 15 years full time education

About The Role Project Role : Application Lead Project Role Description : Lead the effort to design, build and configure applications, acting as the primary point of contact. Must have skills : SAP ABAP Cloud Good to have skills : SAP ABAP Development for HANAMinimum 7.5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an Application Lead, you will lead the effort to design, build, and configure applications, acting as the primary point of contact. You will be responsible for managing the team and ensuring successful project delivery. Your typical day will involve collaborating with multiple teams, making key decisions, and providing solutions to problems for your immediate team and across multiple teams. Roles & Responsibilities:- Expected to be an SME-Design, build and configure applications to meet business process and application requirements.-Review and revise technical designs to meet ABAP project requirements-Recommend process improvements to achieve project goals-Provide high quality support during unit testing, integration testing, User Acceptance, and deployment solution throughout the project - Collaborate and manage the team to perform- Responsible for team decisions- Engage with multiple teams and contribute to key decisions- Provide solutions to problems for their immediate team and across multiple teams- Lead the effort to design, build, and configure applications- Act as the primary point of contact for the project- Manage the team and ensure successful project delivery- Collaborate with multiple teams to make key decisions- Provide solutions to problems for the immediate team and across multiple teams Professional & Technical Skills: - Must To Have Skills: Proficiency in SAP HCM On Premise ABAP- Good To Have Skills: Experience with SAP ABAP Development for HANA, SAP HCM PayrollExcellent in SAP-HR-ABAP and worked on all sub modules of HCM as a technical consultant-Should have extensively worked on SAP Time Management and SAP Payroll with good knowledge in analyzing Time Evaluation log and Payroll driver log. -Good experience in CR handling and new requirements.-Strong knowledge of core ABAP Programming Reports, Interface, Function Modules, Data Dictionary, Dialog Programming, BADIs, ALV OOPs, Workflow and Process & Forms.-Good experience in Logical Database PNP, PNPCE, PCH programming and worked on ABAP tool like Infotype creation enhancement, Features, PU12, Adhoc query, HR Forms, ALE-IDoc ,Code Inspector. Strong understanding of statistical analysis and machine learning algorithms- Experience with data visualization tools such as Tableau or Power BI- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity Additional Information:- The candidate should have a minimum of 7.5 years of experience in SAP HCM On Premise ABAP- This position is based at our Bengaluru office- A 15 years full-time education is required Qualification 15 years full time education

About The Role Project Role : Technology Educator Project Role Description : Instrumental in keeping technology talent market relevant, by upskilling and cross skilling them. Primarily responsible for delivering foundational training in technology, delivery, professional development and industry content. Contribute to course content development and creation of questions for certification and assessments. Must have skills : Machine Learning Good to have skills : NAMinimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Technology Educator, you will play a crucial role in keeping the technology talent market relevant by upskilling and cross-skilling individuals. Your responsibilities will include delivering foundational training in technology, professional development, and industry content, as well as contributing to course content development and assessment creation. Roles & Responsibilities:- Expected to be an SME.- Collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Provide solutions to problems for their immediate team and across multiple teams.- Develop and implement innovative training programs.- Evaluate training effectiveness and make necessary adjustments.- Stay updated on industry trends and incorporate relevant content into training programs. Professional & Technical Skills: - Must To Have Skills: Proficiency in Machine Learning.- Strong understanding of statistical analysis and machine learning algorithms.- Experience with data visualization tools such as Tableau or Power BI.- Hands-on experience implementing various machine learning algorithms.- Solid grasp of data munging techniques for data quality and integrity. Additional Information:- The candidate should have a minimum of 5 years of experience in Machine Learning.- This position is based at our Bengaluru office.- A 15 years full-time education is required. Qualification 15 years full time education

About The Role Project Role : Software Development Engineer Project Role Description : Analyze, design, code and test multiple components of application code across one or more clients. Perform maintenance, enhancements and/or development work. Must have skills : Microsoft Robotic Process Automation Advanced Good to have skills : NAMinimum 7.5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an Application Lead, you will lead the effort to design, build, and configure applications, acting as the primary point of contact. You will be responsible for managing the team and ensuring successful project delivery. Your typical day will involve collaborating with multiple teams, making key decisions, and providing solutions to problems for your immediate team and across multiple teams. Roles & Responsibilities:- Expected to be an SME- Collaborate and manage the team to perform- Responsible for team decisions- Engage with multiple teams and contribute to key decisions- Provide solutions to problems for their immediate team and across multiple teams- Lead the effort to design, build, and configure applications- Act as the primary point of contact for the project- Manage the team and ensure successful project delivery- Collaborate with multiple teams to make key decisions- Provide solutions to problems for the immediate team and across multiple teams Professional & Technical Skills: - Must To Have Skills: Proficiency in Microsoft Robotic Process Automation advanced; Blue Prism- Strong understanding of statistical analysis and machine learning algorithms- Experience with data visualization tools such as Tableau or Power BI- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity Additional Information:- The candidate should have a minimum of 7.5 years of experience in Microsoft Robotic Process Automation- This position is based in Hyderabad Qualification 15 years full time education