233 Erwin Jobs - Page 3

We are looking for a skilled Data Modeler to design, develop, and manage scalable and high-performing data models that support enterprise-wide analytics and reporting needs. In this individual contributor role, you ll work closely with data engineers, architects, and business stakeholders to understand data requirements and translate them into well-structured conceptual, logical, and physical data models.

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.

Hi Candidates, we have job openings in one of our MNC Company Interested candidates can apply here and share details to chandrakala.c@i-q.co Note: NP-0-15 days only serving Role & responsibilities Key Responsibilities Complete Data Modelling Tasks o Initiate and manage Gap Analysis and Source-to-Target Mapping Exercises. o Gain a comprehensive understanding of the EA extract. o Map the SAP source used in EA extracts to the AWS Transform Zone, AWS Conform Zone, and AWS Enrich Zone. Develop a matrix view of all Excel/Tableau reports to identify any missing fields or tables from SAP in the Transform Zone. Engage with SMEs to finalize the Data Model (DM). Obtain email confirmation and approval for the finalized DM. o Perform data modelling using ER Studio and STTM. o Generate DDL scripts for data engineers to facilitate implementation. Complete Data Engineering Tasks o Set up infrastructure for pipelines this includes Glue Jobs, crawlers, scheduling, step functions etc. Build, deploy, test and run pipelines on demand in lower environments. Verify data integrity: no duplicates, all columns in final table etc. Write unit tests for methods used in pipeline and use standard tools for testing. o Code formatting and linting. o Collaborate with other Modelling Engineers to align on correct approach. o Update existing pipelines for CZ tables (SDLF and OF) where necessary with new columns if they are required for EZ tables. Raise DDP requests to register databases and tables, and to load data into the raw zone. Create comprehensive good documentation. Ensure each task is accompanied by detailed notes specific to its functional area for clear tracking and reference. Analyse and manage bugs, and change requests raised by business/SMEs. Collaborate with Data Analyst and Virtual Engineers (VE) to refine and enhance semantic modelling in Power BI. Plan out work using Microsoft Azure, ADO. Dependencies, status and effort is correctly reflected. Required Skills and Experience: Proven experience in data modelling and data pipeline development. Proficiency with tools like ER Studio, STTM, AWS Glue, Redshift & Athena, and Power BI. Strong SQL and experience with generating DDL scripts. Experience working in SAP data environments. Experience in any of these domain areas is highly desirable: Logistics, Supply Planning, Exports and IFOT. Familiarity with cloud platforms, particularly AWS. Hands-on experience with DevOps and Agile methodologies (e.g., Azure ADO). Strong communication and documentation skills. Ability to work collaboratively with cross-functional teams. Preferred candidate profile

Overview Enterprise Data Operations Analyst Job OverviewAs an Analyst, Data Modeling , your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analyzing project data needs, identifying data storage and integration needs/issues, and driving opportunities for data model reuse, satisfying project requirements. Role will advocate Enterprise Architecture, Data Design, and D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architects teams. As a member of the data modeling team, you will create data models for very large and complex data applications in public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics . The primary responsibilities of this role are to work with data product owners, data management owners, and data engineering teams to create physical and logical data models with an extensible philosophy to support future, unknown use cases with minimal rework. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. You will establish data design patterns that will drive flexible, scalable, and efficient data models to maximize value and reuse. Responsibilities Responsibilities Complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, EMR, Spark, DataBricks , Snowflake, Azure Synapse or other Cloud data warehousing technologies. Governs data design/ modeling documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned. Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting. Supports assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices, and tools. Contributes to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development. Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework. Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives , maximizes reuse. Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper managementbusiness and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations. Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development. Assist with data planning, sourcing, collection, profiling, and transformation. Create Source To Target Mappings for ETL and BI developers. Show expertise for data at all levelslow-latency, relational, and unstructured data stores; analytical and data lakes; data streaming (consumption/production), data in-transit. Develop reusable data models based on cloud-centric, code-first approaches to data management and cleansing. Partner with the Data Governance team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders. Support data lineage and mapping of source system data to canonical data stores for research, analysis and productization. Qualifications Qualifications 5+ years of overall technology experience that includes at least 2+ years of data modeling and systems architecture. Around 2+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 2+ years of experience developing enterprise data models. Experience in building solutions in the retail or in the supply chain space. Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models). Experience with integration of multi cloud services (Azure) with on-premises technologies. Experience with data profiling and data quality tools like Apache Griffin, Deequ , and Great Expectations. Experience building/ operating highly available , distributed systems of data extraction, ingestion, and processing of large data sets. Experience with at least one MPP database technology such as Redshift, Synapse, Teradata or SnowFlake . Experience with version control systems like Github and deployment & CI tools. Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus. Experience of metadata management, data lineage, and data glossaries is a plus. Working knowledge of agile development, including DevOps and DataOps concepts. Familiarity with business intelligence tools (such as PowerBI ).

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

Overview As an Analyst, Data Modeling, your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analyzing project data needs, identifying data storage and integration needs/issues, and driving opportunities for data model reuse, satisfying project requirements. Role will advocate Enterprise Architecture, Data Design, and D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architects teams. As a member of the data modeling team, you will create data models for very large and complex data applications in public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics. The primary responsibilities of this role are to work with data product owners, data management owners, and data engineering teams to create physical and logical data models with an extensible philosophy to support future, unknown use cases with minimal rework. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. You will establish data design patterns that will drive flexible, scalable, and efficient data models to maximize value and reuse. Responsibilities Complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, EMR, Spark, DataBricks, Snowflake, Azure Synapse or other Cloud data warehousing technologies. Governs data design/modeling documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned. Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting. Supports assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices, and tools. Contributes to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development. Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework. Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives, maximizes reuse. Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper managementbusiness and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations. Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development. Assist with data planning, sourcing, collection, profiling, and transformation. Create Source To Target Mappings for ETL and BI developers. Show expertise for data at all levelslow-latency, relational, and unstructured data stores; analytical and data lakes; data streaming (consumption/production), data in-transit. Develop reusable data models based on cloud-centric, code-first approaches to data management and cleansing. Partner with the Data Governance team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders. Support data lineage and mapping of source system data to canonical data stores for research, analysis and productization. Qualifications 4+ years of overall technology experience that includes at least 2+ years of data modeling and systems architecture. Around 2+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 2+ years of experience developing enterprise data models. Experience in building solutions in the retail or in the supply chain space. Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models). Experience with integration of multi cloud services (Azure) with on-premises technologies. Experience with data profiling and data quality tools like Apache Griffin, Deequ, and Great Expectations. Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets. Experience with at least one MPP database technology such as Redshift, Synapse, Teradata or SnowFlake. Experience with version control systems like Github and deployment & CI tools. Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus. Experience of metadata management, data lineage, and data glossaries is a plus. Working knowledge of agile development, including DevOps and DataOps concepts. Familiarity with business intelligence tools (such as PowerBI).

Overview Enterprise Data Operations Sr Analyst L08 Job OverviewAs Senior Analyst, Data Modeling , your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analyzing project data needs, identifying data storage and integration needs/issues, and driving opportunities for data model reuse, satisfying project requirements. Role will advocate Enterprise Architecture, Data Design, and D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architects teams. As a member of the data modeling team, you will create data models for very large and complex data applications in public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics . The primary responsibilities of this role are to work with data product owners, data management owners, and data engineering teams to create physical and logical data models with an extensible philosophy to support future, unknown use cases with minimal rework. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. You will establish data design patterns that will drive flexible, scalable, and efficient data models to maximize value and reuse. Responsibilities Responsibilities Complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, EMR, Spark, DataBricks , Snowflake, Azure Synapse or other Cloud data warehousing technologies. Governs data design/ modeling documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned. Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting. Supports assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices, and tools. Contributes to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development. Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework. Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives , maximizes reuse. Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper managementbusiness and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations. Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development. Assist with data planning, sourcing, collection, profiling, and transformation. Create Source To Target Mappings for ETL and BI developers. Show expertise for data at all levelslow-latency, relational, and unstructured data stores; analytical and data lakes; data streaming (consumption/production), data in-transit. Develop reusable data models based on cloud-centric, code-first approaches to data management and cleansing. Partner with the Data Governance team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders. Support data lineage and mapping of source system data to canonical data stores for research, analysis and productization. Qualifications Qualifications 8+ years of overall technology experience that includes at least 4+ years of data modeling and systems architecture. 3+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 4+ years of experience developing enterprise data models. Experience in building solutions in the retail or in the supply chain space. Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models). Experience with integration of multi cloud services (Azure) with on-premises technologies. Experience with data profiling and data quality tools like Apache Griffin, Deequ , and Great Expectations. Experience building/ operating highly available , distributed systems of data extraction, ingestion, and processing of large data sets. Experience with at least one MPP database technology such as Redshift, Synapse, Teradata or SnowFlake . Experience with version control systems like Github and deployment & CI tools. Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus. Experience of metadata management, data lineage, and data glossaries is a plus. Working knowledge of agile development, including DevOps and DataOps concepts. Familiarity with business intelligence tools (such as PowerBI ). Does the person hired for this job need to be based in a PepsiCo office, or can they be remote Employee must be based in a Pepsico office Primary Work LocationHyderabad HUB-IND

Overview As an Analyst, Data Modeling, your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analyzing project data needs, identifying data storage and integration needs/issues, and driving opportunities for data model reuse, satisfying project requirements. Role will advocate Enterprise Architecture, Data Design, and D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architects teams. As a member of the data modeling team, you will create data models for very large and complex data applications in public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics. The primary responsibilities of this role are to work with data product owners, data management owners, and data engineering teams to create physical and logical data models with an extensible philosophy to support future, unknown use cases with minimal rework. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. You will establish data design patterns that will drive flexible, scalable, and efficient data models to maximize value and reuse. Responsibilities Complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, EMR, Spark, DataBricks, Snowflake, Azure Synapse or other Cloud data warehousing technologies. Governs data design/modeling documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned. Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting. Supports assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices, and tools. Contributes to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development. Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework. Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives, maximizes reuse. Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper managementbusiness and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations. Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development. Assist with data planning, sourcing, collection, profiling, and transformation. Create Source To Target Mappings for ETL and BI developers. Show expertise for data at all levelslow-latency, relational, and unstructured data stores; analytical and data lakes; data streaming (consumption/production), data in-transit. Develop reusable data models based on cloud-centric, code-first approaches to data management and cleansing. Partner with the Data Governance team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders. Support data lineage and mapping of source system data to canonical data stores for research, analysis and productization. Qualifications 5+ years of overall technology experience that includes at least 2+ years of data modeling and systems architecture. Around 2+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 2+ years of experience developing enterprise data models. Experience in building solutions in the retail or in the supply chain space. Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models). Experience with integration of multi cloud services (Azure) with on-premises technologies. Experience with data profiling and data quality tools like Apache Griffin, Deequ, and Great Expectations. Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets. Experience with at least one MPP database technology such as Redshift, Synapse, Teradata or SnowFlake. Experience with version control systems like Github and deployment & CI tools. Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus. Experience of metadata management, data lineage, and data glossaries is a plus. Working knowledge of agile development, including DevOps and DataOps concepts. Familiarity with business intelligence tools (such as PowerBI).

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

Highly skilled and experienced Data Modeler to join Enterprise Data Modelling team. The candidate will be responsible for creating and maintaining conceptual logical and physical data models ensuring alignment with industry best practices and standards. Working closely with business and functional teams the Data Modeler will play a pivotal role in standardizing data models at portfolio and domain levels driving efficiencies and maximizing the value of clients data assets. Preference will be given to candidates with prior experience within an Enterprise Data Modeling team. The ideal domain experience would be Insurance or Investment Banking. Roles and Responsibilities: Develop comprehensive conceptual logical and physical data models for multiple domains within the organization leveraging industry best practices and standards. Collaborate with business and functional teams to understand their data requirements and translate them into effective data models that support their strategic objectives. Serve as a subject matter expert in data modeling tools such as ERwin Data Modeler providing guidance and support to other team members and stakeholders. Establish and maintain standardized data models across portfolios and domains ensuring consistency governance and alignment with organizational objectives. Identify opportunities to optimize existing data models and enhance data utilization particularly in critical areas such as fraud banking AML. Provide consulting services to internal groups on data modeling tool usage administration and issue resolution promoting seamless data flow and application connections. Develop and deliver training content and support materials for data models ensuring that stakeholders have the necessary resources to understand and utilize them effectively. Collaborate with the enterprise data modeling group to develop and implement a robust governance framework and metrics for model standardization with a focus on longterm automated monitoring solutions. Qualifications: Bachelors or masters degree in computer science Information Systems or a related field. 10 years of experience working as a Data Modeler or in a similar role preferably within a large enterprise environment. Expertise in data modeling concepts and methodologies with demonstrated proficiency in creating conceptual logical and physical data models. Handson experience with data modeling tools such as Erwin Data Modeler as well as proficiency in database environments such as Snowflake and Netezza. Strong analytical and problemsolving skills with the ability to understand complex data requirements and translate them into effective data models. Excellent communication and collaboration skills with the ability to work effectively with crossfunctional teams and stakeholders. problem-solving skills,business intelligence platforms,erwin,data modeling,database management systems,data warehousing,etl processes,big data technologies,agile methodologies,data governance,sql,enterprise data modelling,data visualization tools,cloud data services,analytical skills,data modelling tool,,data architecture,communication skills

As a Senior member of Front-end Experience’s Enablement team, you will provide support and enablement for delivering complex, cross-product UI features across portfolio of products. You’ll work closely with engineers and designers across the company to leverage your experience and expertise in building accessible, delightful, and maintainable UIs. What you’ll do (responsibilities): Deliver on feature requests that unblock customers and facilitate deals, enhancing the product's user experience. Collaborate closely with Design, Product, and other cross-functional teams to innovate and deliver high-quality, customer-centric solutions. Maintain high standards of software quality within the team by establishing good practices and habits. Develop and implement well-tested solutions to ensure reliability and performance. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise 10-14 years of software engineering experience with a proven track record of technical or engineering lead roles. Experience with diverse technology stacks and project types is preferred. Proficiency in JavaScript is necessary. Experience with the Ember framework is preferred, or a strong interest and ability to get up to speed with it. Extensive experience with cloud computing platforms (AWS, Azure, GCP) and infrastructure as code (Terraform). Strong interest in customer-focused work, with experience collaborating with Design and Product Management functions to deliver impactful solutions. Demonstrated ability to tackle complex technical challenges and deliver innovative solutions. Excellent communication and collaboration skills, with a focus on customer satisfaction and team success. Proven ability to lead by example, mentor junior engineers, and contribute to a positive team culture. Commitment to developing well-tested solutions to ensure high reliability and performance.

As a Senior member of Front-end Experience’s Enablement team, you will provide support and enablement for delivering complex, cross-product UI features across portfolio of products. You’ll work closely with engineers and designers across the company to leverage your experience and expertise in building accessible, delightful, and maintainable UIs. What you’ll do (responsibilities): Deliver on feature requests that unblock customers and facilitate deals, enhancing the product's user experience. Collaborate closely with Design, Product, and other cross-functional teams to innovate and deliver high-quality, customer-centric solutions. Maintain high standards of software quality within the team by establishing good practices and habits. Develop and implement well-tested solutions to ensure reliability and performance. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise 5-9 years of software engineering experience with a proven track record of technical or engineering lead roles. Experience with diverse technology stacks and project types is preferred. Proficiency in JavaScript is necessary. Experience with the Ember framework is preferred, or a strong interest and ability to get up to speed with it. Extensive experience with cloud computing platforms (AWS, Azure, GCP) and infrastructure as code (Terraform). Strong interest in customer-focused work, with experience collaborating with Design and Product Management functions to deliver impactful solutions. Demonstrated ability to tackle complex technical challenges and deliver innovative solutions. Excellent communication and collaboration skills, with a focus on customer satisfaction and team success. Proven ability to lead by example, mentor junior engineers, and contribute to a positive team culture. Commitment to developing well-tested solutions to ensure high reliability and performance.

Senior Data Modelller About the Role: We are seeking an experienced Senior Data Modeller to join our team. In this role, you will be responsible for designing and standardization of enterprise-wide data models across multiple domains such as Customer, Product, Billing, and Network. The ideal candidate will work closely with cross-functional teams to translate business needs into scalable and governed data structures. You will work closely with customers, and technology partners to deliver data solutions that address complex business requirements including customer experience management, network optimization, revenue assurance, and digital transformation initiatives. Responsibilities: Design logical and physical data models aligned with enterprise and industry standards Create and maintain data models for Customer, Product, Usage, and Service domains Translate business requirements into normalized and analytical schemas (Star/Snowflake) Define and maintain entity relationships, hierarchy levels (Customer - Account - MSISDN), and attribute lineage Standardize attribute definitions across systems and simplify legacy structures Collaborate with engineering teams to implement models in cloud data platforms (e.g., Databricks) Collaborate with domain stewards to simplify and standardize legacy data structures Work with governance teams to tag attributes for privacy, compliance, and data quality Document metadata, lineage, and maintain version control of data models Support analytics, reporting, and machine learning teams by enabling standardized data access Design solutions leveraging Microsoft Azure and Databricks for telecom data processing and analytics Qualifications: Bachelors or masters degree in computer science, Data Science, or a related technical field 7+ years of experience in data modelling roles Hands-on experience building data models and platforms Strong experience with data modeling tools (Erwin,Azure Analysis services, SSAS, dbt, informatica) Hands-on experience with modern cloud data platforms (Databricks, Azure Synapse, Snowflake) Deep understanding of data warehousing concepts and normalized/denormalized models Expertise in SQL, data profiling, schema design, and metadata documentation Familiarity with domain-driven design, data mesh and modular architecture Experience in large-scale transformation or modernization programs Knowledge of regulatory frameworks such as GDPR or data privacy-by-design

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 DB Schema). Functional knowledge of the mutual fund industry is a plus. Familiarity with GCP databases like Alloy DB, Cloud SQL, and Big Query. Willingness to work from Chennai (office presence is mandatory) Chennai customer site, requiring five days of on-site work each week. Mandatory Skills: Cloud-PaaS-GCP-Google Cloud Platform Experience: 5-8 Years

Experience with machine learning environments and LLMs Certification in IBM watsonx.data or related IBM data and AI technologies Experience with integrating watsonx.data with GenAI or LLM initiatives (e.g., RAG architectures). Hands-on experience with Lakehouse platform (e.g., Databricks, Snowflake) Having exposure to implement or understanding of DB replication process Experience with NoSQL databases (e.g., MongoDB, Cassandra). Experience in data modeling tools (e.g., ER/Studio, ERwin). Knowledge of data governance and compliance standards (e.g., GDPR, HIPAA).Soft Skills Having Database Administration skills Experience with data security, backup, and disaster recovery strategies. Implementing WLM on any of the databases (preferably DB2) Experience implementing data governance frameworks, including metadata management and data cataloging tools.

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 : Remote (India). Employment Type : Contract (Remote). Experience Required : 7+ Years. 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.

Roles and Responsibilities Design and develop data models using Erwin/Data Modeling tools to meet business requirements. Collaborate with stakeholders to gather requirements and ensure data model aligns with business needs. Develop and maintain data governance policies, procedures, and standards for the organization. Provide guidance on best practices for data management and analytics initiatives. Participate in project planning, execution, and delivery of projects related to data modeling. Desired Candidate Profile 7-12 years of experience in Data Modeling or a related field (e.g., database design). Strong understanding of Erwin/Data Modeling tools (e.g., Erwin/Snowflake) and ability to apply them effectively. Experience working with large datasets and developing complex data models for various industries (BFSI preferred). Excellent communication skills with ability to work collaboratively across multiple teams. Proven track record of delivering high-quality results under tight deadlines.

Responsibilities: Identify & understand business requirements for Reporting, design, and implement future proof8 solutions, optimizing data delivery, etc. Solution-based thinking in the DWH design and integration / optimization of the existing designs related to DWHv Together with the Business end users and the contact persons of a specific domain / capability, responsible for building a standard & sustainable DWH solution Thinking along and involvement in the E2E DWH design (everything needed for this) to help build reports and dashboards for our partners in an insightful and efficient way Support the ETL engineers in translating the functional requirement into technical designs Responsible for the delivery and follow-up of the solutions within the lifecycle management Coaching/Training team members on various processes - BI analysis Profile: Should have atleast 6+ years of experience in business requirements analysis (Reporting) for BI projects Should be able to understand & convert business requirements (functional) into logical & physical DWH models (Star, Snowflake) using Kimball methodologyv Should be proficient in understanding DWH databases, expertise in analysing & writing complex SQLs in an efficient way Strong working experience in Data Modelling tools - erwin Data Modeller or SAP Powerdesigner is a must Assemble large, complex data sets that meet functional / non-functional business requirements

Greetings from Sight Spectrum Technologies!! As discussed over the call, we are processing your profile for the skillset of Data Modelling We would like to ensure that you are interested in this position. Exp : 8+ years Location: Remote Skills : Data Modeler Description: At Least 2 Projects done as Data Modeler Employ Entity-Relationship modeling with the intent of producing a design best suited for retrospective analysis of data.existing business system data, data profiling and source analysis. Expert using SQL Experts in understanding business need to translate those needs into an effective model. Expert in Entity-Relationship modeling, with specific expertise in Star/Snowflake Schema modeling. Experience implementing IBM UDMH Model - Atomic or Dimensional Model Exposure in one or more enterprise-level Modeling tools, IDA, ERWin, ER-Studio, etc Healthcare Domain Knowledge is a must; Exposure to HL7, FHIR, OMOP will be a plus if interested kindly share your resume to roopavahini@sightspectrum.in

As a PySpark Data Engineer, you must have a minimum of 2 years of experience in PySpark. Strong programming skills in Python, PySpark, and Scala are preferred. It is essential to have experience in designing and implementing CI/CD, Build Management, and Development strategies. Additionally, familiarity with SQL and SQL Analytical functions is required, along with participation in key business, architectural, and technical decisions. There is an opportunity for training in AWS cloud technology. In the role of a Python Developer, a minimum of 2 years of experience in Python/PySpark is necessary. Strong programming skills in Python, PySpark, and Scala are preferred. Experience in designing and implementing CI/CD, Build Management, and Development strategies is essential. Familiarity with SQL and SQL Analytical functions and participation in key business, architectural, and technical decisions are also required. There is a potential for training in AWS cloud technology. As a Senior Software Engineer at Capgemini, you should have over 3 years of experience in Scala with a strong project track record. Hands-on experience in Scala/Spark development and SQL writing skills on RDBMS (DB2) databases are crucial. Experience in working with different file formats like JSON, Parquet, AVRO, ORC, and XML is preferred. Previous involvement in a HDFS platform development project is necessary. Proficiency in data analysis, data profiling, and data lineage, along with strong oral and written communication skills, is required. Experience in Agile projects is a plus. For the position of Data Modeler, expertise in data structures, algorithms, calculus, linear algebra, machine learning, and modeling is essential. Knowledge of data warehousing concepts such as Star schema, snowflake, or data vault for data mart or data warehousing is required. Proficiency in using data modeling software like Erwin, ER studio, MySQL Workbench to produce logical and physical data models is necessary. Hands-on knowledge and experience with tools like PL/SQL, PySpark, Hive, Impala, and other scripting tools are preferred. Experience with Software Development Lifecycle using the Agile methodology is essential. Strong communication and stakeholder management skills are crucial for this role. In this role, you will design, develop, and optimize PL/SQL procedures, functions, triggers, and packages. You will also write efficient SQL queries, joins, and subqueries for data retrieval and manipulation. Additionally, you will develop and maintain database objects such as tables, views, indexes, and sequences. Optimizing query performance and troubleshooting database issues to improve efficiency are key responsibilities. Collaboration with application developers, business analysts, and system architects to understand database requirements is essential. Ensuring data integrity, consistency, and security within Oracle databases is also a crucial aspect of the role. Developing ETL processes and scripts for data migration and integration are part of the responsibilities. Documenting database structures, stored procedures, and coding best practices is required. Staying up-to-date with Oracle database technologies, best practices, and industry trends is essential for success in this role.,

Location : Remote (India). 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.

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.

HashiCorp, an IBM Company solves development, operations, and security challenges in infrastructure so organizations can focus on business-critical tasks. We build products to give organizations a consistent way to manage their move to cloud-based IT infrastructures for running their applications. Our products enable companies large and small to mix and match AWS, Microsoft Azure, Google Cloud, and other clouds as well as on-premises environments, easing their ability to deliver new applications. At HashiCorp, we have used the Tao of HashiCorp as our guiding principles for product development and operate according to a strong set of company principles for how we interact with each other. We value top-notch collaboration and communication skills, both among internal teams and in how we interact with our users. What you’ll do (responsibilities) As a Senior Engineer, you will contribute to the development, operation, and enhancement of cloud offerings. With at least 8 years of experience in software engineering, cloud computing, and operational excellence, you will play a vital role in ensuring our managed services are reliable, scalable, and secure, meeting the sophisticated needs of our global customer base. Contribute to the architecture, development, and scaling of dataplane services, ensuring best practices in cloud service delivery. Implement robust monitoring and alerting frameworks to guarantee high availability and performance of our managed services. Work closely with product teams, platform teams, and security to align development efforts, enhance product integrations, and ensure a cohesive user experience. Leverage feedback from customers and support teams to drive product enhancements, focusing on reducing operational toil and improving service usability. Partner with the security team to fortify service security and comply with regulatory standards, maintaining HashiCorp’s reputation for trust and reliability. Stay at the forefront of cloud technologies and practices, advocating for and implementing solutions that enhance our managed service offerings. Required education Bachelor's Degree Required technical and professional expertise 8+ years of software engineering experience, with a focus on cloud services and infrastructure. Proficiency in Go, with experience in other languages (Python, Ruby etc) considered a plus. Extensive knowledge of cloud computing platforms (AWS, Azure, GCP) and experience with infrastructure as code (Terraform). Demonstrated ability in developing and managing production-grade cloud services, with a strong understanding of operational reliability and security practices. Excellent problem-solving skills, with the ability to collaborate effectively across diverse teams. Passionate about improving operational processes and delivering customer-centric solutions. Preferred technical and professional experience Familiarity with HashiCorp and IBM products and services.