167 Erwin Jobs

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

Synechron is seeking a knowledgeable and proactive Data Modeler to guide the design and development of data structures that support our clients' business objectives. In this role, you will collaborate with cross-functional teams to translate business requirements into scalable and efficient data models, ensuring data accuracy, consistency, and integrity. You will contribute to creating sustainable and compliant data architectures that leverage emerging technologies such as cloud, IoT, mobile, and blockchain. Your work will be instrumental in enabling data-driven decision-making and operational excellence across projects.Software Required Skills: Strong understanding of data modeling concepts, methodologies, and tools Experience with data modeling for diverse technology platforms including cloud, mobile, IoT, and blockchain Familiarity with database management systems (e.g., relational, NoSQL) Knowledge of SDLC and Agile development practices Proficiency in modeling tools such as ERwin, PowerDesigner, or similar Preferred Skills: Experience with data integration tools and ETL processes Knowledge of data governance and compliance standards Familiarity with cloud platforms (AWS, Azure, GCP) and how they impact data architectureOverall Responsibilities Collaborate with business analysts, data engineers, and stakeholders to understand data requirements and translate them into robust data models Design logical and physical data models optimized for performance, scalability, and maintainability Develop and maintain documentation for data structures, including data dictionaries and metadata Conduct reviews of data models and code to ensure adherence to quality standards and best practices Assist in designing data security and privacy measures in alignment with organizational policies Stay informed about emerging data modeling trends and incorporate best practices into project delivery Support data migration, integration, and transformation activities as needed Provide technical guidance and mentorship related to data modeling standardsTechnical Skills (By Category) Data Modeling & Data Management: EssentialLogical/physical data modeling, ER diagrams, data dictionaries PreferredDimensional modeling, data warehousing, master data management Programming Languages: PreferredSQL (expertise in writing complex queries) OptionalPython, R for data analysis and scripting Databases & Data Storage Technologies: EssentialRelational databases (e.g., Oracle, SQL Server, MySQL) PreferredNoSQL (e.g., MongoDB, Cassandra), cloud-native data stores Cloud Technologies: PreferredBasic understanding of cloud data solutions (AWS, Azure, GCP) Frameworks & Libraries: Not typically required, but familiarity with data integration frameworks is advantageous Development Tools & Methodologies: EssentialData modeling tools (ERwin, PowerDesigner), version control (Git), Agile/Scrum workflows Security & Compliance: Knowledge of data security best practices, regulatory standards like GDPR, HIPAAExperience Minimum of 8+ years of direct experience in data modeling, data architecture, or related roles Proven experience designing data models for complex systems across multiple platforms (cloud, mobile, IoT, blockchain) Experience working in Agile environments using tools like JIRA, Confluence, Git Preference for candidates with experience supporting data governance and data quality initiativesNoteEquivalent demonstrated experience in relevant projects or certifications can qualify candidates.Day-to-Day Activities Participate in daily stand-ups and project planning sessions Collaborate with cross-functional teams to understand and analyze business requirements Create, review, and refine data models and associated documentation Develop data schemas, dictionaries, and standards to ensure consistency Support data migration, integration, and performance tuning activities Conduct peer reviews and provide feedback on data models and solutions Keep current with the latest industry developments in data architecture and modeling Troubleshoot and resolve data-related technical issuesQualifications Bachelors or Masters degree in Computer Science, Data Science, Information Technology, or related fields Demonstrated experience with data modeling tools and techniques in diverse technological environments Certifications related to data modeling, data management, or cloud platforms (preferred)Professional Competencies Strong analytical and critical thinking skills to develop optimal data solutions Effective communication skills for translating technical concepts to non-technical stakeholders Ability to work independently and in collaborative team environments Skilled problem solver able to handle complex data challenges Adaptability to rapidly evolving technologies and project requirements Excellent time management and prioritization skills to deliver quality outputs consistently

Synechron is seeking a knowledgeable and proactive Data Modeler to guide the design and development of data structures that support our clients' business objectives. In this role, you will collaborate with cross-functional teams to translate business requirements into scalable and efficient data models, ensuring data accuracy, consistency, and integrity. You will contribute to creating sustainable and compliant data architectures that leverage emerging technologies such as cloud, IoT, mobile, and blockchain. Your work will be instrumental in enabling data-driven decision-making and operational excellence across projects.Software Required Skills: Strong understanding of data modeling concepts, methodologies, and tools Experience with data modeling for diverse technology platforms including cloud, mobile, IoT, and blockchain Familiarity with database management systems (e.g., relational, NoSQL) Knowledge of SDLC and Agile development practices Proficiency in modeling tools such as ERwin, PowerDesigner, or similar Preferred Skills: Experience with data integration tools and ETL processes Knowledge of data governance and compliance standards Familiarity with cloud platforms (AWS, Azure, GCP) and how they impact data architectureOverall Responsibilities Collaborate with business analysts, data engineers, and stakeholders to understand data requirements and translate them into robust data models Design logical and physical data models optimized for performance, scalability, and maintainability Develop and maintain documentation for data structures, including data dictionaries and metadata Conduct reviews of data models and code to ensure adherence to quality standards and best practices Assist in designing data security and privacy measures in alignment with organizational policies Stay informed about emerging data modeling trends and incorporate best practices into project delivery Support data migration, integration, and transformation activities as needed Provide technical guidance and mentorship related to data modeling standardsTechnical Skills (By Category) Data Modeling & Data Management: EssentialLogical/physical data modeling, ER diagrams, data dictionaries PreferredDimensional modeling, data warehousing, master data management Programming Languages: PreferredSQL (expertise in writing complex queries) OptionalPython, R for data analysis and scripting Databases & Data Storage Technologies: EssentialRelational databases (e.g., Oracle, SQL Server, MySQL) PreferredNoSQL (e.g., MongoDB, Cassandra), cloud-native data stores Cloud Technologies: PreferredBasic understanding of cloud data solutions (AWS, Azure, GCP) Frameworks & Libraries: Not typically required, but familiarity with data integration frameworks is advantageous Development Tools & Methodologies: EssentialData modeling tools (ERwin, PowerDesigner), version control (Git), Agile/Scrum workflows Security & Compliance: Knowledge of data security best practices, regulatory standards like GDPR, HIPAAExperience Minimum of 8+ years of direct experience in data modeling, data architecture, or related roles Proven experience designing data models for complex systems across multiple platforms (cloud, mobile, IoT, blockchain) Experience working in Agile environments using tools like JIRA, Confluence, Git Preference for candidates with experience supporting data governance and data quality initiativesNoteEquivalent demonstrated experience in relevant projects or certifications can qualify candidates.Day-to-Day Activities Participate in daily stand-ups and project planning sessions Collaborate with cross-functional teams to understand and analyze business requirements Create, review, and refine data models and associated documentation Develop data schemas, dictionaries, and standards to ensure consistency Support data migration, integration, and performance tuning activities Conduct peer reviews and provide feedback on data models and solutions Keep current with the latest industry developments in data architecture and modeling Troubleshoot and resolve data-related technical issuesQualifications Bachelors or Masters degree in Computer Science, Data Science, Information Technology, or related fields Demonstrated experience with data modeling tools and techniques in diverse technological environments Certifications related to data modeling, data management, or cloud platforms (preferred)Professional Competencies Strong analytical and critical thinking skills to develop optimal data solutions Effective communication skills for translating technical concepts to non-technical stakeholders Ability to work independently and in collaborative team environments Skilled problem solver able to handle complex data challenges Adaptability to rapidly evolving technologies and project requirements Excellent time management and prioritization skills to deliver quality outputs consistently

Project description We are seeking a highly skilled Data Modelling Expert with deep experience in the Avaloq Core Banking platform to join our technology team. The ideal candidate will be responsible for designing, maintaining, and optimizing complex data models that support our banking products, client data, and regulatory reporting needs. This role requires a blend of domain expertise in banking and wealth management, strong data architecture capabilities, and hands-on experience working with the Avaloq platform. Responsibilities Design, implement, and maintain conceptual, logical, and physical data models within the Avaloq Core Banking system. Collaborate with business analysts, product owners, and Avaloq parameterisation teams to translate business requirements into robust data models. Ensure alignment of data models with Avaloq's object model and industry best practices. Perform data profiling, quality checks, and lineage tracing to support regulatory and compliance requirements (e.g., Basel III, MiFID II, ESG). Support integration of Avaloq data with downstream systems (e.g., CRM, data warehouses, reporting platforms). Provide expert input on data governance, metadata management, and model documentation. Contribute to change requests, upgrades, and data migration projects involving Avaloq. Collaborate with cross-functional teams to drive data consistency, reusability, and scalability. Review and validate existing data models, identify gaps or optimisation opportunities. Ensure data models meet performance, security, and privacy requirements. Skills Must have Proven experience (5+ years) in data modelling or data architecture, preferably within financial services. 3+ years of hands-on experience with Avaloq Core Banking Platform, especially its data structures and object model. Strong understanding of relational databases and data modelling tools (e.g., ER/Studio, ERwin, or similar). Proficient in SQL and data manipulation in Avaloq environments. Knowledge of banking products, client lifecycle data, and regulatory data requirements. Familiarity with data governance, data quality, and master data management concepts. Experience working in Agile or hybrid project delivery environments. Nice to have Exposure to Avaloq Scripting or parameterisation is a strong plus. Experience integrating Avaloq with data lakes, BI/reporting tools, or regulatory platforms. Understanding of data privacy regulations (GDPR, FINMA, etc.). Certification in Avaloq or relevant financial data management domains is advantageous. Other Languages EnglishC1 Advanced Seniority Senior

Project Role : Data Modeler Project Role Description : Work with key business representatives, data owners, end users, application designers and data architects to model current and new data. Must have skills : Data Modeling Techniques and Methodologies Good to have skills : NAMinimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Project Role :Data Architect & Modeler Project Role Description Data Model, Design, build and lead the complex ETL data integration pipelines to meet business process and application requirements. Management Level :9Work Experience :6+ yearsWork Location :AnyMust have skills :Data Architecture Principles Good to have skills :Data Modeling, Data Architect, Informatica PowerCenter, Informatica Data Quality, SAP BusinessObjects Data Services, SQL, PL/SQL, SAP HANA DB, MS Azure, Python, ErWin, SAP Power Designer Job :Data Architect, Modeler, and data Integration LeadKey Responsibilities:1) Working on building Data models, Forward and Reverse Engineering.2) Working on Data and design analysis and working with data analysts team on data model design.3) Working on presentations on design, end to end flow and data models.4) Work on new and existing data models using Power designer tools and other designing tools like Visio5) Work with functional SMEs, BAs to review requirements, mapping documents Technical Experience:1) Should have good understanding of ETL design concepts like CDC, SCD, Transpose/ pivot, Updates, Validation2) Should have strong understanding of SQL concepts, Data warehouse concepts and can easily understand data technically and functionally.3) Good understanding of various file formats like xml, delimited, fixed width etc.4) Understand the concepts of data quality, data cleansing, data profiling5) Good to have Python and other new data technologies and cloud exposure.6) Having Insurance background is a plus. Educational Qualification :15 years of fulltime education with BE/B Tech or equivalent Professional & Technical Skills: - Must To Have Skills: Proficiency in Data Modeling Techniques and Methodologies.- Strong understanding of relational and non-relational database design principles.- Experience with data integration and ETL processes.- Familiarity with data governance and data quality frameworks.- Ability to translate business requirements into technical specifications. Qualification 15 years full time education

Project Role : Commercial PMO Operator Project Role Description : Plan and manage commercial deliverables for client accounts and help reduce overall project costs by improving efficiency and standardizing the processes throughout the contracts life. Assist commercial and/or account leadership in executing the commercial vision for the account. Must have skills : Data Modeling Techniques and Methodologies Good to have skills : NAMinimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :Data Modelling, Data Entity-Relationship design and build, Schema setup Tools:ERWIN, DatabricksAs a Commercial PMO Operator, you will plan and manage commercial deliverables for client accounts, reduce project costs, and standardize processes. Assist in executing the commercial vision for the account, contributing to overall efficiency and success. 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- Implement strategies to enhance project efficiency- Analyze and optimize commercial processes- Develop and maintain project cost reduction initiatives Professional & Technical Skills: - Must To Have Skills: Proficiency in Data Modeling Techniques and Methodologies- Strong understanding of project management principles- Experience in financial analysis and cost reduction strategies- Knowledge of commercial operations and contract management- Excellent communication and interpersonal skills Additional Information:- The candidate should have a minimum of 5 years of experience in Data Modeling Techniques and Methodologies- This position is based at our Bengaluru office- A 15 years full time education is required Qualification 15 years full time education

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.