233 Erwin Jobs - Page 7

Job Summary : We are looking for a highly skilled Data Engineer / Data Modeler with strong experience in Snowflake, DBT, and GCP to support our data infrastructure and modeling initiatives. The ideal candidate should possess excellent SQL skills, hands-on experience with Erwin Data Modeler, and a strong background in modern data architectures and data modeling techniques. Key Responsibilities : - Design and implement scalable data models using Snowflake and Erwin Data Modeler. - Create, maintain, and enhance data pipelines using DBT and GCP (BigQuery, Cloud Storage, Dataflow). - Perform reverse engineering on existing systems (e.g., Sailfish/DDMS) using DBeaver or similar tools to understand and rebuild data models. - Develop efficient SQL queries and stored procedures for data transformation, quality, and validation. - Collaborate with business analysts and stakeholders to gather data requirements and convert them into physical and logical models. - Ensure performance tuning, security, and optimization of the Snowflake data warehouse. - Document metadata, data lineage, and business logic behind data structures and flows. - Participate in code reviews, enforce coding standards, and provide best practices for data modeling and governance. Must-Have Skills : - Snowflake architecture, schema design, and data warehouse experience. - DBT (Data Build Tool) for data transformation and pipeline development. - Strong expertise in SQL (query optimization, complex joins, window functions, etc.) - Hands-on experience with Erwin Data Modeler (logical and physical modeling). - Experience with GCP (BigQuery, Cloud Composer, Cloud Storage). - Experience in reverse engineering legacy systems like Sailfish or DDMS using DBeaver. Good To Have : - Experience with CI/CD tools and DevOps for data environments. - Familiarity with data governance, security, and privacy practices. - Exposure to Agile methodologies and working in distributed teams. - Knowledge of Python for data engineering tasks and orchestration scripts. Soft Skills : - Excellent problem-solving and analytical skills. - Strong communication and stakeholder management. - Self-driven with the ability to work independently in a remote setup.

Job Summary : We are looking for a highly skilled Data Engineer / Data Modeler with strong experience in Snowflake, DBT, and GCP to support our data infrastructure and modeling initiatives. The ideal candidate should possess excellent SQL skills, hands-on experience with Erwin Data Modeler, and a strong background in modern data architectures and data modeling techniques. Key Responsibilities : - Design and implement scalable data models using Snowflake and Erwin Data Modeler. - Create, maintain, and enhance data pipelines using DBT and GCP (BigQuery, Cloud Storage, Dataflow). - Perform reverse engineering on existing systems (e.g., Sailfish/DDMS) using DBeaver or similar tools to understand and rebuild data models. - Develop efficient SQL queries and stored procedures for data transformation, quality, and validation. - Collaborate with business analysts and stakeholders to gather data requirements and convert them into physical and logical models. - Ensure performance tuning, security, and optimization of the Snowflake data warehouse. - Document metadata, data lineage, and business logic behind data structures and flows. - Participate in code reviews, enforce coding standards, and provide best practices for data modeling and governance. Must-Have Skills : - Snowflake architecture, schema design, and data warehouse experience. - DBT (Data Build Tool) for data transformation and pipeline development. - Strong expertise in SQL (query optimization, complex joins, window functions, etc.) - Hands-on experience with Erwin Data Modeler (logical and physical modeling). - Experience with GCP (BigQuery, Cloud Composer, Cloud Storage). - Experience in reverse engineering legacy systems like Sailfish or DDMS using DBeaver. Good To Have : - Experience with CI/CD tools and DevOps for data environments. - Familiarity with data governance, security, and privacy practices. - Exposure to Agile methodologies and working in distributed teams. - Knowledge of Python for data engineering tasks and orchestration scripts. Soft Skills : - Excellent problem-solving and analytical skills. - Strong communication and stakeholder management. - Self-driven with the ability to work independently in a remote setup.

Employment Type : Contract (Remote). Job Summary : We are looking for a highly skilled Data Engineer / Data Modeler with strong experience in Snowflake, DBT, and GCP to support our data infrastructure and modeling initiatives. The ideal candidate should possess excellent SQL skills, hands-on experience with Erwin Data Modeler, and a strong background in modern data architectures and data modeling techniques. Key Responsibilities : - Design and implement scalable data models using Snowflake and Erwin Data Modeler. - Create, maintain, and enhance data pipelines using DBT and GCP (BigQuery, Cloud Storage, Dataflow). - Perform reverse engineering on existing systems (e.g., Sailfish/DDMS) using DBeaver or similar tools to understand and rebuild data models. - Develop efficient SQL queries and stored procedures for data transformation, quality, and validation. - Collaborate with business analysts and stakeholders to gather data requirements and convert them into physical and logical models. - Ensure performance tuning, security, and optimization of the Snowflake data warehouse. - Document metadata, data lineage, and business logic behind data structures and flows. - Participate in code reviews, enforce coding standards, and provide best practices for data modeling and governance. Must-Have Skills : - Snowflake architecture, schema design, and data warehouse experience. - DBT (Data Build Tool) for data transformation and pipeline development. - Strong expertise in SQL (query optimization, complex joins, window functions, etc.) - Hands-on experience with Erwin Data Modeler (logical and physical modeling). - Experience with GCP (BigQuery, Cloud Composer, Cloud Storage). - Experience in reverse engineering legacy systems like Sailfish or DDMS using DBeaver. Good To Have : - Experience with CI/CD tools and DevOps for data environments. - Familiarity with data governance, security, and privacy practices. - Exposure to Agile methodologies and working in distributed teams. - Knowledge of Python for data engineering tasks and orchestration scripts. Soft Skills : - Excellent problem-solving and analytical skills. - Strong communication and stakeholder management. - Self-driven with the ability to work independently in a remote setup.

Employment Type : Contract (Remote). Job Summary : We are looking for a highly skilled Data Engineer / Data Modeler with strong experience in Snowflake, DBT, and GCP to support our data infrastructure and modeling initiatives. The ideal candidate should possess excellent SQL skills, hands-on experience with Erwin Data Modeler, and a strong background in modern data architectures and data modeling techniques. Key Responsibilities : - Design and implement scalable data models using Snowflake and Erwin Data Modeler. - Create, maintain, and enhance data pipelines using DBT and GCP (BigQuery, Cloud Storage, Dataflow). - Perform reverse engineering on existing systems (e.g., Sailfish/DDMS) using DBeaver or similar tools to understand and rebuild data models. - Develop efficient SQL queries and stored procedures for data transformation, quality, and validation. - Collaborate with business analysts and stakeholders to gather data requirements and convert them into physical and logical models. - Ensure performance tuning, security, and optimization of the Snowflake data warehouse. - Document metadata, data lineage, and business logic behind data structures and flows. - Participate in code reviews, enforce coding standards, and provide best practices for data modeling and governance. Must-Have Skills : - Snowflake architecture, schema design, and data warehouse experience. - DBT (Data Build Tool) for data transformation and pipeline development. - Strong expertise in SQL (query optimization, complex joins, window functions, etc.) - Hands-on experience with Erwin Data Modeler (logical and physical modeling). - Experience with GCP (BigQuery, Cloud Composer, Cloud Storage). - Experience in reverse engineering legacy systems like Sailfish or DDMS using DBeaver. Good To Have : - Experience with CI/CD tools and DevOps for data environments. - Familiarity with data governance, security, and privacy practices. - Exposure to Agile methodologies and working in distributed teams. - Knowledge of Python for data engineering tasks and orchestration scripts. Soft Skills : - Excellent problem-solving and analytical skills. - Strong communication and stakeholder management. - Self-driven with the ability to work independently in a remote setup.

Location : Chennai (Mandatory)@ Customer location - 5 days from office Exp. : 8-10 Years JD: Data Modeller Should have real time data modelling experience into 2-3 projects Hands-on experience in data modelling for both OLTP and OLAP systems. In-depth knowledge of Conceptual, Logical, and Physical data modelling. Strong understanding of indexing, partitioning, and data sharding with practical experience. Experience in identifying and addressing factors affecting database performance for near-real-time reporting and application interaction. Proficiency with at least one data modelling tool (preferably DBSchema). Functional knowledge of the mutual fund industry is a plus. Familiarity with GCP databases like AlloyDB, CloudSQL, and BigQuery. Willingness to work from Chennai (office presence is mandatory). Exp- Currrent CTC Expected CTC NP-

Role: Data Modelling Fulltime (Work from office Monday to Friday) Location: Chennai Minimum Qualifications: Bachelors Degree or experience in Engineering, 5+ years of experience in data architecture or a related field, with a strong understanding of cloud-based data solutions Proficiency in designing and implementing Medallion Architecture with bronze, silver, and gold layers Experienced curating and Erwin modeling data into Star Schemas Strong background in semantic modeling and creating meaningful, user-friendly data sets Experience with AWS , Synapse, and Power BI. Work visa sponsorship is not available for this position

Overview Prodapt is looking for a Data Model Architect. The candidate should be good with design and data architecture in Telecom domain. Responsibilities Deliverables Design & Document – Data Model for CMDB, P-S-R Catalogue (Product, Service and Resource management layer) Design & Document Build Interface Speciation for Data Integration. Activities Data Architecture and Modeling Design and maintain conceptual, logical, and physical data models Ensure scalability and adaptability of data models for future organizational needs. Data Model P-S-R catalogs in the existing Catalogs,SOM,COM systems CMDB Design and Management Architect and optimize the CMDB to accurately reflect infrastructure components, telecom assets, and their relationships. Define data governance standards and enforce data consistency across the CMDB. Design data integrations between across systems (e.g., OSS/BSS, network monitoring tools, billing systems). Good Communication skills. Bachelors Degree.

Req ID: 310007 We are currently seeking a Digital Engineering Staff Engineer to join our team in Bangalore, Karntaka (IN-KA), India (IN). Data Modeler Position Overview: The Data Modeler will be responsible for designing and implementing data models that support the organization's data management and analytics needs. This role involves collaborating with various stakeholders to understand data sources, relationships, and business requirements, and translating them into effective data structures. Key Responsibilities: Collaborate with Business Analysts: Understand different data sources and their relationships. Prepare Conformed Dimension Matrix: Identify different grains of facts, finalize dimensions, and harmonize data across sources. Create Data Models: Develop Source to Target Mapping (STMs) documentation and custom mappings (both technical and non-technical). Include Transformation Rules: Ensure STMs include pseudo SQL queries for transformation rules. Coordinate Reviews: Work with Data Architects, Product Owners, and Enablement teams to review and approve models, STMs, and custom mappings. Engage with Data Engineers: Clarify any questions related to STMs and custom mappings. Required Technical Skills: Proficiency in SQL: Strong understanding of SQL and database management systems. Data Modeling Tools: Familiarity with tools such as ERwin, IBM InfoSphere Data Architect, or similar. Data Warehousing Concepts: Solid knowledge of data warehousing principles, ETL processes, and OLAP. Data Governance and Compliance: Understanding of data governance frameworks and compliance requirements. Key Competencies: Analytical Skills: Ability to analyze complex data sets and derive meaningful insights. Attention to Detail: Ensure accuracy and consistency in data models. Communication Skills: Effectively collaborate with stakeholders and articulate technical concepts to non-technical team members. Project Management Skills: Ability to prioritize tasks, manage timelines, and coordinate with cross-functional teams. Continuous Learning and Adaptability: Commitment to ongoing professional development and adaptability to changing business needs and technologies. Additional : Problem-Solving Abilities: Innovative solutions to data integration, quality, and performance challenges. Knowledge of Data Modeling Methodologies: Entity-relationship modeling, dimensional modeling, normalization techniques. Familiarity with Business Intelligence Tools: Enhance ability to design data structures that facilitate data analysis and visualization. Preferred Qualifications: Experience in SDLC: Understanding of all phases of the Software Development Life Cycle. Certifications: Relevant certifications in data modeling, data warehousing, or related fields.

Data/ETL Architect/Data Modeler: Develop conceptual, logical, and physical data models to ensure accurate, scalable, and optimized data structures aligned with business requirements. Collaborate with business and technical teams to define data flow, transformation rules, and ensure alignment with data governance and quality standards. Design end-to-end ETL architecture and data integration solutions. Technologies - SQL, ETL, Big Data, ER Studio Role & responsibilities Preferred candidate profile

Role - Data Modeler/Senior Data Modeler Exp - 5 to 12 Yrs Locs - Hyderabad, Pune, Bengaluru Position - Permanent Must have skills: - Strong SQL - Strong Data Warehousing skills - ER/Relational/Dimensional Data Modeling - Data Vault Modeling - OLAP, OLTP - Schemas & Data Marts Good to have skills: - Data Vault - ERwin / ER Studio - Cloud Platforms (AWS or Azure)

5 years of DataStage experience. Strong Data warehousing knowledge and ready to provide guidance to junior members in the team. Must have a good communication skill as the role demands lot of interaction with US Business team as well as IT stakeholders. Must be able to work independently handle multiple concurrent tasks with an ability to prioritize and manage tasks effectively. Experience in developing DataStage jobs and deploying the jobs thru SDLC cycle. Knowledge of data modeling database design and the data warehousing ecosystem. Ability to work independently and collaborate with others at all levels of technical understanding. Analyzing organizational data requirements and reviewing/Understanding logical and physical Data Flow Diagrams and Entity Relationship Diagrams using tools such as Visio and Erwin Designing and building scalable DataStage solutions. Updating data within repositories and data warehouses. Assisting project leaders in determining project timelines and objectives. Monitoring jobs and identifying bottlenecks in the data processing pipeline. Testing and troubleshooting problems in system designs and processes. Proficiency in SQL or another relevant coding language. Has great communication and reasoning skills including the ability to make a strong case for technology choices. 5+ years of experience in testing debugging skills and troubleshooting support and development issues

Locations - Pune/Bangalore/Hyderabad/Indore Contract duration- 6 months Responsibilities Be responsible for the development of the conceptual, logical, and physical data models, the implementation of RDBMS, operational data store (ODS), data marts, and data lakes on target platforms. Implement business and IT data requirements through new data strategies and designs across all data platforms (relational & dimensional - MUST and NoSQL-optional) and data tools (reporting, visualization, analytics, and machine learning). Work with business and application/solution teams to implement data strategies, build data flows, and develop conceptual/logical/physical data models Define and govern data modeling and design standards, tools, best practices, and related development for enterprise data models. Identify the architecture, infrastructure, and interfaces to data sources, tools supporting automated data loads, security concerns, analytic models, and data visualization. Hands-on modeling, design, configuration, installation, performance tuning, and sandbox POC. Work proactively and independently to address project requirements and articulate issues/challenges to reduce project delivery risks. Must have Payments Background Skills Hands-on relational, dimensional, and/or analytic experience (using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols). Experience with data warehouse, data lake, and enterprise big data platforms in multi-data-center contexts required. Good knowledge of metadata management, data modeling, and related tools (Erwin or ER Studio or others) required. Experience in team management, communication, and presentation. Experience with Erwin, Visio or any other relevant tool.

Skill Set Required GCP, Data Modelling (OLTP, OLAP), indexing, DBSchema, CloudSQL, BigQuery Data Modeller - Hands-on data modelling for OLTP and OLAP systems. In-Depth knowledge of Conceptual, Logical and Physical data modelling. Strong understanding of Indexing, partitioning, data sharding with practical experience of having done the same. Strong understanding of variables impacting database performance for near-real time reporting and application interaction. Should have working experience on at least one data modelling tool, preferably DBSchema. People with functional knowledge of the mutual fund industry will be a plus. Good understanding of GCP databases like AlloyDB, CloudSQL and BigQuery.

Translates business needs into a data model, providing expertise on data modeling tools and techniques for designing data models for applications and related systems. Skills include logical and physical data modeling, and knowledge of ERWin, MDM, and/or ETL. Data modeling is a process used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Translates business needs into a data model, providing expertise on data modeling tools and techniques for designing data models for applications and related systems. Skills include logical and physical data modeling, and knowledge of ERWin, MDM, and/or ETL. Data modeling is a process used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations. Therefore, the process of data modeling involves professional data modelers working closely with business stakeholders, as well as potential users of the information system. There are three different types of data models produced while progressing from requirements to the actual database to be used for the information system. Preferred technical and professional experience Translates business needs into a data model, providing expertise on data modeling tools and techniques for designing data models for applications and related systems. Skills include logical and physical data modeling, and knowledge of ERWin, MDM, and/or ETL. Data modeling is a process used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations.

As an Data Engineer at IBM you will harness the power of data to unveil captivating stories and intricate patterns. You'll contribute to data gathering, storage, and both batch and real-time processing. Collaborating closely with diverse teams, you'll play an important role in deciding the most suitable data management systems and identifying the crucial data required for insightful analysis. As a Data Engineer, you'll tackle obstacles related to database integration and untangle complex, unstructured data sets. In this role, your responsibilities may include Implementing and validating predictive models as well as creating and maintain statistical models with a focus on big data, incorporating a variety of statistical and machine learning techniques Designing and implementing various enterprise search applications such as Elasticsearch and Splunk for client requirements Work in an Agile, collaborative environment, partnering with other scientists, engineers, consultants and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviours. Build teams or writing programs to cleanse and integrate data in an efficient and reusable manner, developing predictive or prescriptive models, and evaluating modelling results Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise 4+ years of experience in data modelling, data architecture. Proficiency in data modelling tools ERwin, IBM Infosphere Data Architect and database management systems Familiarity with different data models like relational, dimensional and NoSQl databases. Understanding of business processes and how data supports business decision making. Strong understanding of database design principles, data warehousing concepts, and data governance practices Preferred technical and professional experience Excellent analytical and problem-solving skills with a keen attention to detail. Ability to work collaboratively in a team environment and manage multiple projects simultaneously. Knowledge of programming languages such as SQL

As an Data Engineer at IBM you will harness the power of data to unveil captivating stories and intricate patterns. You'll contribute to data gathering, storage, and both batch and real-time processing. Collaborating closely with diverse teams, you'll play an important role in deciding the most suitable data management systems and identifying the crucial data required for insightful analysis. As a Data Engineer, you'll tackle obstacles related to database integration and untangle complex, unstructured data sets. In this role, your responsibilities may include: Implementing and validating predictive models as well as creating and maintain statistical models with a focus on big data, incorporating a variety of statistical and machine learning techniques Designing and implementing various enterprise search applications such as Elasticsearch and Splunk for client requirements Work in an Agile, collaborative environment, partnering with other scientists, engineers, consultants and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviours. Build teams or writing programs to cleanse and integrate data in an efficient and reusable manner, developing predictive or prescriptive models, and evaluating modelling results Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise 4+ years of experience in data modelling, data architecture. Proficiency in data modelling tools ERwin, IBM Infosphere Data Architect and database management systems Familiarity with different data models like relational, dimensional and NoSQl databases. Understanding of business processes and how data supports business decision making. Strong understanding of database design principles, data warehousing concepts, and data governance practices Preferred technical and professional experience Excellent analytical and problem-solving skills with a keen attention to detail. Ability to work collaboratively in a team environment and manage multiple projects simultaneously. Knowledge of programming languages such as SQL

Key Responsibilities : Design and develop data models to support business intelligence and analytics solutions. Work with Erwin or Erwin Studio to create, manage, and optimize conceptual, logical, and physical data models. Implement Dimensional Modelling techniques for data warehousing and reporting. Collaborate with business analysts, data engineers, and stakeholders to gather and understand data requirements. Ensure data integrity, consistency, and compliance with Banking domain standards. Work with Snowflake to develop and optimize cloud-based data models. Write and execute complex SQL queries for data analysis and validation. Identify and resolve data quality issues and inconsistencies. Required Skills & Qualifications : 7+ years of experience in Data Modelling and Data Analysis. Strong expertise in Erwin or Erwin Studio for data modeling. Experience with Dimensional Modelling and Data Warehousing (DWH) concepts. Proficiency in Snowflake and SQL for data management and querying. Previous experience in the Banking domain is mandatory. Strong analytical and problem-solving skills. Ability to work independently in a remote environment. Excellent verbal and written communication skills.

Data Science Machine Learning Deep Learning Python NLP statistical exp Roles and responsibilities Experience in Data Modelling RPython SQL Data Science Machine Learning Deep Learning NLP Statistics Have ability to solve Business problems using Data Should possess extensiveknowledge of and experience in applying data mining and machine learning techniques on large amount of datasets High level of proficiency in statisticaltools like R Python Candidate will be expected to communicate analyticalresults in a way that is meaningful for business stakeholders and provides actionable insights Have the ability to discover new opportunities whereadvanced analytical techniques can be leveraged for solving business problems

Key Responsibilities : Design and develop data models to support business intelligence and analytics solutions. Work with Erwin or Erwin Studio to create, manage, and optimize conceptual, logical, and physical data models. Implement Dimensional Modelling techniques for data warehousing and reporting. Collaborate with business analysts, data engineers, and stakeholders to gather and understand data requirements. Ensure data integrity, consistency, and compliance with Banking domain standards. Work with Snowflake to develop and optimize cloud-based data models. Write and execute complex SQL queries for data analysis and validation. Identify and resolve data quality issues and inconsistencies. Required Skills & Qualifications : 7+ years of experience in Data Modelling and Data Analysis. Strong expertise in Erwin or Erwin Studio for data modeling. Experience with Dimensional Modelling and Data Warehousing (DWH) concepts. Proficiency in Snowflake and SQL for data management and querying. Previous experience in the Banking domain is mandatory. Strong analytical and problem-solving skills. Ability to work independently in a remote environment. Excellent verbal and written communication skills.

Key Responsibilities : Design and develop data models to support business intelligence and analytics solutions. Work with Erwin or Erwin Studio to create, manage, and optimize conceptual, logical, and physical data models. Implement Dimensional Modelling techniques for data warehousing and reporting. Collaborate with business analysts, data engineers, and stakeholders to gather and understand data requirements. Ensure data integrity, consistency, and compliance with Banking domain standards. Work with Snowflake to develop and optimize cloud-based data models. Write and execute complex SQL queries for data analysis and validation. Identify and resolve data quality issues and inconsistencies. Required Skills & Qualifications : 7+ years of experience in Data Modelling and Data Analysis. Strong expertise in Erwin or Erwin Studio for data modeling. Experience with Dimensional Modelling and Data Warehousing (DWH) concepts. Proficiency in Snowflake and SQL for data management and querying. Previous experience in the Banking domain is mandatory. Strong analytical and problem-solving skills. Ability to work independently in a remote environment. Excellent verbal and written communication skills.

Key Responsibilities : Design and develop data models to support business intelligence and analytics solutions. Work with Erwin or Erwin Studio to create, manage, and optimize conceptual, logical, and physical data models. Implement Dimensional Modelling techniques for data warehousing and reporting. Collaborate with business analysts, data engineers, and stakeholders to gather and understand data requirements. Ensure data integrity, consistency, and compliance with Banking domain standards. Work with Snowflake to develop and optimize cloud-based data models. Write and execute complex SQL queries for data analysis and validation. Identify and resolve data quality issues and inconsistencies. Required Skills & Qualifications : 7+ years of experience in Data Modelling and Data Analysis. Strong expertise in Erwin or Erwin Studio for data modeling. Experience with Dimensional Modelling and Data Warehousing (DWH) concepts. Proficiency in Snowflake and SQL for data management and querying. Previous experience in the Banking domain is mandatory. Strong analytical and problem-solving skills. Ability to work independently in a remote environment. Excellent verbal and written communication skills.

Overview As a Data Modeler & Functional Data Senior Analyst, your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analysing 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, D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architecture 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 Master Data, Finance, Revenue Management, Supply chain, Manufacturing and Logistics. The primary responsibility of this role is 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-premises 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, Data Bricks, Snowflake, Azure Synapse or other Cloud data warehousing technologies. Governs Data Design/Modeling documentation of metadata (business definitions of entities and attributes) and construction of 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 existing, or new, applications/reporting. Lead and Support assigned project contractors (both on & offshore), 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 enhancements or new development. Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework. Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for proper management ofbusiness 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. Analyze/profile source data and identify issues that impact accuracy, completeness, consistency, integrity, timeliness and validity. Create Source to Target Mapping documents including identifying and documenting data transformations. Assume accountability and responsibility for assigned product delivery, be flexible and able to work with ambiguity, changing priorities, tight timelines and critical situations/issues. 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 BA or BS degree required in Data Science/Management/Engineering, Business Analytics, Information Systems, Software Engineering or related Technology Discipline. 8+ years of overall technology experience that includes at least 4+ years of Data Modeling and Systems Architecture/Integration. 3+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 4+ years of experience developing Enterprise Data Models. 3+ years of Functional experience with SAP Master Data Governance (MDG) including use of T-Codes to create/update records and query tables. Extensive knowledge of all core Master Data tables, Reference Tables, IDoc structures. 3+ years of experience with Customer & Supplier Master Data. Strong SQL skills with ability to understand and write complex queries. Strong understanding of Data Life cycle, Integration and Master Data Management principles. Excellent verbal and written communication and collaboration skills. Strong Excel skills for data analysis and manipulation. Strong analytical and problem-solving skills. 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. Working knowledge of agile development, including Dev Ops and Data Ops concepts. Experience mapping disparate data sources into a common canonical model. Differentiating Competencies Experience with metadata management, data lineage and data glossaries. Experience with Azure Data Factory, Databricks and Azure Machine learning. Familiarity with business intelligence tools (such as Power BI). CPG industry experience. Experience with Material, Location, Finance, Supply Chain, Logistics, Manufacturing & Revenue Management Data.

Overview As an Analyst, Data Modeler, your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analysing 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-premises 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, Data Bricks, 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 Bachelors degree required in Computer Science, Data Management/Analytics/Science, Information Systems, Software Engineering or related Technology Discipline. 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 Dev Ops and Data Ops concepts. Familiarity with business intelligence tools (such as Power BI). Excellent verbal and written communication and collaboration skills.

Key Responsibilities : Design and develop data models to support business intelligence and analytics solutions. Work with Erwin or Erwin Studio to create, manage, and optimize conceptual, logical, and physical data models. Implement Dimensional Modelling techniques for data warehousing and reporting. Collaborate with business analysts, data engineers, and stakeholders to gather and understand data requirements. Ensure data integrity, consistency, and compliance with Banking domain standards. Work with Snowflake to develop and optimize cloud-based data models. Write and execute complex SQL queries for data analysis and validation. Identify and resolve data quality issues and inconsistencies. Required Skills & Qualifications : 7+ years of experience in Data Modelling and Data Analysis. Strong expertise in Erwin or Erwin Studio for data modeling. Experience with Dimensional Modelling and Data Warehousing (DWH) concepts. Proficiency in Snowflake and SQL for data management and querying. Previous experience in the Banking domain is mandatory. Strong analytical and problem-solving skills. Ability to work independently in a remote environment. Excellent verbal and written communication skills.

Key Responsibilities : Design and develop data models to support business intelligence and analytics solutions. Work with Erwin or Erwin Studio to create, manage, and optimize conceptual, logical, and physical data models. Implement Dimensional Modelling techniques for data warehousing and reporting. Collaborate with business analysts, data engineers, and stakeholders to gather and understand data requirements. Ensure data integrity, consistency, and compliance with Banking domain standards. Work with Snowflake to develop and optimize cloud-based data models. Write and execute complex SQL queries for data analysis and validation. Identify and resolve data quality issues and inconsistencies. Required Skills & Qualifications : 7+ years of experience in Data Modelling and Data Analysis. Strong expertise in Erwin or Erwin Studio for data modeling. Experience with Dimensional Modelling and Data Warehousing (DWH) concepts. Proficiency in Snowflake and SQL for data management and querying. Previous experience in the Banking domain is mandatory. Strong analytical and problem-solving skills. Ability to work independently in a remote environment. Excellent verbal and written communication skills.