Job description

Job Description: Azure Lead Data Engineer + Guidewire Role Overview

We are seeking an experienced Azure Lead Data Engineer with Guidewire expertise to lead the design, development, and delivery of scalable data engineering solutions for insurance and enterprise data platforms. The ideal candidate will have strong hands-on experience with Azure Data Factory (ADF), Azure Data Lake, Snowflake, DBT, SQL, and cloud-based data integration, along with a solid understanding of Guidewire InsuranceSuite data and integrations.

The candidate will provide technical leadership, work closely with business and technology stakeholders, and ensure the delivery of reliable, high-performance, and governed data pipelines.

Key Responsibilities

Lead the design and development of scalable ETL/ELT data pipelines using Azure Data Factory, Snowflake, DBT, and other Azure data services.
Design and manage data integration workflows from multiple source systems, including Guidewire applications and insurance data platforms, into Snowflake and Azure-based data environments.
Analyze and understand Guidewire data models, business entities, policy, claims, billing, underwriting, and related insurance datasets.
Develop efficient and optimized SQL queries for data extraction, transformation, validation, and reporting.
Lead technical discussions with business stakeholders, Guidewire teams, architects, and data consumers to translate business requirements into scalable technical solutions.
Provide technical leadership and guidance to data engineering team members and review code, data models, and pipeline designs.
Monitor, troubleshoot, and optimize data pipelines to ensure high performance, reliability, scalability, and availability.
Implement and enforce data quality, governance, metadata, lineage, and documentation standards.
Develop and maintain reusable data engineering frameworks and best practices.
Collaborate with data architects, analysts, DevOps, QA, and cloud engineering teams in a cloud-native environment.
Support migration and modernization of legacy insurance data platforms into Azure and Snowflake.
Implement and support CI/CD processes for data engineering workflows.
Ensure data solutions comply with enterprise security, governance, and regulatory requirements.

Must-Have Skills

8+ years of experience in Data Engineering, Data Integration, or related roles.
Strong hands-on experience with the Azure Cloud Platform and Azure data services.
Proven expertise in Azure Data Factory (ADF) for designing, orchestrating, automating, and monitoring complex data pipelines.
Strong experience with Azure Data Lake Storage (ADLS) and cloud-based data integration architectures.
Extensive experience with SQL, including complex queries, performance optimization, and data transformation.
Hands-on experience with Snowflake and SnowSQL for cloud data warehousing and data engineering.
Strong working knowledge of DBT (Data Build Tool) for data transformation, testing, and documentation.
Experience working with large-scale and complex enterprise datasets.
Strong understanding of Guidewire InsuranceSuite, Guidewire data models, or Guidewire-based data integrations.
Experience working with insurance domain data such as Policy, Claims, Billing, Customer, Producer, and Underwriting data.
Strong problem-solving, communication, stakeholder management, and technical leadership skills.

Guidewire-Specific Requirements

Experience integrating data from Guidewire applications into enterprise data platforms.
Strong understanding of Guidewire data structures and insurance business processes.
Experience with Guidewire PolicyCenter, ClaimCenter, and/or BillingCenter data is highly preferred.
Ability to work with Guidewire APIs, extracts, events, or integration mechanisms where applicable.
Experience in designing downstream data pipelines and analytics solutions for Guidewire-generated data.
Understanding of insurance data governance, reconciliation, and data quality requirements.

Good-to-Have Skills

Experience with Azure Synapse Analytics.
Experience with Azure Functions.
Knowledge of Python and/or PySpark for custom data transformations and engineering solutions.
Experience with Databricks is an added advantage.
Experience with legacy technologies such as DataStage or Netezza.
Strong understanding of CI/CD pipelines and DevOps practices for data workflows.
Experience with data governance, metadata management, data catalog, and data lineage tools.
Exposure to Power BI, Tableau, or other BI and analytics tools.
Experience in insurance industry data modernization and cloud migration projects.

Qualifications

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
8+ years of experience in Data Engineering with strong exposure to Azure and cloud data platforms.
Demonstrated experience leading data engineering teams or providing technical leadership on enterprise data projects.
Strong understanding of modern cloud data architecture, ETL/ELT, data warehousing, and data governance.
Excellent communication and collaboration skills with the ability to work across business and technical teams.

Key Responsibilities

Lead the design and development of scalable ETL/ELT data pipelines using Azure Data Factory, Snowflake, DBT, and other Azure data services.
Design and manage data integration workflows from multiple source systems, including Guidewire applications and insurance data platforms, into Snowflake and Azure-based data environments.
Analyze and understand Guidewire data models, business entities, policy, claims, billing, underwriting, and related insurance datasets.
Develop efficient and optimized SQL queries for data extraction, transformation, validation, and reporting.
Lead technical discussions with business stakeholders, Guidewire teams, architects, and data consumers to translate business requirements into scalable technical solutions.
Provide technical leadership and guidance to data engineering team members and review code, data models, and pipeline designs.
Monitor, troubleshoot, and optimize data pipelines to ensure high performance, reliability, scalability, and availability.
Implement and enforce data quality, governance, metadata, lineage, and documentation standards.
Develop and maintain reusable data engineering frameworks and best practices.
Collaborate with data architects, analysts, DevOps, QA, and cloud engineering teams in a cloud-native environment.
Support migration and modernization of legacy insurance data platforms into Azure and Snowflake.
Implement and support CI/CD processes for data engineering workflows.
Ensure data solutions comply with enterprise security, governance, and regulatory requirements.

Must-Have Skills

8+ years of experience in Data Engineering, Data Integration, or related roles.
Strong hands-on experience with the Azure Cloud Platform and Azure data services.
Proven expertise in Azure Data Factory (ADF) for designing, orchestrating, automating, and monitoring complex data pipelines.
Strong experience with Azure Data Lake Storage (ADLS) and cloud-based data integration architectures.
Extensive experience with SQL, including complex queries, performance optimization, and data transformation.
Hands-on experience with Snowflake and SnowSQL for cloud data warehousing and data engineering.
Strong working knowledge of DBT (Data Build Tool) for data transformation, testing, and documentation.
Experience working with large-scale and complex enterprise datasets.
Strong understanding of Guidewire InsuranceSuite, Guidewire data models, or Guidewire-based data integrations.
Experience working with insurance domain data such as Policy, Claims, Billing, Customer, Producer, and Underwriting data.
Strong problem-solving, communication, stakeholder management, and technical leadership skills.

Guidewire-Specific Requirements

Experience integrating data from Guidewire applications into enterprise data platforms.
Strong understanding of Guidewire data structures and insurance business processes.
Experience with Guidewire PolicyCenter, ClaimCenter, and/or BillingCenter data is highly preferred.
Ability to work with Guidewire APIs, extracts, events, or integration mechanisms where applicable.
Experience in designing downstream data pipelines and analytics solutions for Guidewire-generated data.
Understanding of insurance data governance, reconciliation, and data quality requirements.

Good-to-Have Skills

Experience with Azure Synapse Analytics.
Experience with Azure Functions.
Knowledge of Python and/or PySpark for custom data transformations and engineering solutions.
Experience with Databricks is an added advantage.
Experience with legacy technologies such as DataStage or Netezza.
Strong understanding of CI/CD pipelines and DevOps practices for data workflows.
Experience with data governance, metadata management, data catalog, and data lineage tools.
Exposure to Power BI, Tableau, or other BI and analytics tools.
Experience in insurance industry data modernization and cloud migration projects.

Qualifications

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
8+ years of experience in Data Engineering with strong exposure to Azure and cloud data platforms.
Demonstrated experience leading data engineering teams or providing technical leadership on enterprise data projects.
Strong understanding of modern cloud data architecture, ETL/ELT, data warehousing, and data governance.
Excellent communication and collaboration skills with the ability to work across business and technical teams.

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Someone shared one job with you. ASAI keeps finding the rest.

Scored, not searched. Every role ranked against your actual profile.

Alerts as often as hourly. Reach new roles while the pile is still small.

Skill gaps, spelled out. See exactly which requirements you don't meet yet.

Verified jobs, only. Say no to ghost jobs. Your time deserves respect.

Job description

Job Description: Azure Lead Data Engineer + Guidewire Role Overview

The candidate will provide technical leadership, work closely with business and technology stakeholders, and ensure the delivery of reliable, high-performance, and governed data pipelines.

Key Responsibilities

Lead the design and development of scalable ETL/ELT data pipelines using Azure Data Factory, Snowflake, DBT, and other Azure data services.
Design and manage data integration workflows from multiple source systems, including Guidewire applications and insurance data platforms, into Snowflake and Azure-based data environments.
Analyze and understand Guidewire data models, business entities, policy, claims, billing, underwriting, and related insurance datasets.
Develop efficient and optimized SQL queries for data extraction, transformation, validation, and reporting.
Lead technical discussions with business stakeholders, Guidewire teams, architects, and data consumers to translate business requirements into scalable technical solutions.
Provide technical leadership and guidance to data engineering team members and review code, data models, and pipeline designs.
Monitor, troubleshoot, and optimize data pipelines to ensure high performance, reliability, scalability, and availability.
Implement and enforce data quality, governance, metadata, lineage, and documentation standards.
Develop and maintain reusable data engineering frameworks and best practices.
Collaborate with data architects, analysts, DevOps, QA, and cloud engineering teams in a cloud-native environment.
Support migration and modernization of legacy insurance data platforms into Azure and Snowflake.
Implement and support CI/CD processes for data engineering workflows.
Ensure data solutions comply with enterprise security, governance, and regulatory requirements.

Must-Have Skills

8+ years of experience in Data Engineering, Data Integration, or related roles.
Strong hands-on experience with the Azure Cloud Platform and Azure data services.
Proven expertise in Azure Data Factory (ADF) for designing, orchestrating, automating, and monitoring complex data pipelines.
Strong experience with Azure Data Lake Storage (ADLS) and cloud-based data integration architectures.
Extensive experience with SQL, including complex queries, performance optimization, and data transformation.
Hands-on experience with Snowflake and SnowSQL for cloud data warehousing and data engineering.
Strong working knowledge of DBT (Data Build Tool) for data transformation, testing, and documentation.
Experience working with large-scale and complex enterprise datasets.
Strong understanding of Guidewire InsuranceSuite, Guidewire data models, or Guidewire-based data integrations.
Experience working with insurance domain data such as Policy, Claims, Billing, Customer, Producer, and Underwriting data.
Strong problem-solving, communication, stakeholder management, and technical leadership skills.

Guidewire-Specific Requirements

Experience integrating data from Guidewire applications into enterprise data platforms.
Strong understanding of Guidewire data structures and insurance business processes.
Experience with Guidewire PolicyCenter, ClaimCenter, and/or BillingCenter data is highly preferred.
Ability to work with Guidewire APIs, extracts, events, or integration mechanisms where applicable.
Experience in designing downstream data pipelines and analytics solutions for Guidewire-generated data.
Understanding of insurance data governance, reconciliation, and data quality requirements.

Good-to-Have Skills

Experience with Azure Synapse Analytics.
Experience with Azure Functions.
Knowledge of Python and/or PySpark for custom data transformations and engineering solutions.
Experience with Databricks is an added advantage.
Experience with legacy technologies such as DataStage or Netezza.
Strong understanding of CI/CD pipelines and DevOps practices for data workflows.
Experience with data governance, metadata management, data catalog, and data lineage tools.
Exposure to Power BI, Tableau, or other BI and analytics tools.
Experience in insurance industry data modernization and cloud migration projects.

Qualifications

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
8+ years of experience in Data Engineering with strong exposure to Azure and cloud data platforms.
Demonstrated experience leading data engineering teams or providing technical leadership on enterprise data projects.
Strong understanding of modern cloud data architecture, ETL/ELT, data warehousing, and data governance.
Excellent communication and collaboration skills with the ability to work across business and technical teams.

Key Responsibilities

Lead the design and development of scalable ETL/ELT data pipelines using Azure Data Factory, Snowflake, DBT, and other Azure data services.
Design and manage data integration workflows from multiple source systems, including Guidewire applications and insurance data platforms, into Snowflake and Azure-based data environments.
Analyze and understand Guidewire data models, business entities, policy, claims, billing, underwriting, and related insurance datasets.
Develop efficient and optimized SQL queries for data extraction, transformation, validation, and reporting.
Lead technical discussions with business stakeholders, Guidewire teams, architects, and data consumers to translate business requirements into scalable technical solutions.
Provide technical leadership and guidance to data engineering team members and review code, data models, and pipeline designs.
Monitor, troubleshoot, and optimize data pipelines to ensure high performance, reliability, scalability, and availability.
Implement and enforce data quality, governance, metadata, lineage, and documentation standards.
Develop and maintain reusable data engineering frameworks and best practices.
Collaborate with data architects, analysts, DevOps, QA, and cloud engineering teams in a cloud-native environment.
Support migration and modernization of legacy insurance data platforms into Azure and Snowflake.
Implement and support CI/CD processes for data engineering workflows.
Ensure data solutions comply with enterprise security, governance, and regulatory requirements.

Must-Have Skills

8+ years of experience in Data Engineering, Data Integration, or related roles.
Strong hands-on experience with the Azure Cloud Platform and Azure data services.
Proven expertise in Azure Data Factory (ADF) for designing, orchestrating, automating, and monitoring complex data pipelines.
Strong experience with Azure Data Lake Storage (ADLS) and cloud-based data integration architectures.
Extensive experience with SQL, including complex queries, performance optimization, and data transformation.
Hands-on experience with Snowflake and SnowSQL for cloud data warehousing and data engineering.
Strong working knowledge of DBT (Data Build Tool) for data transformation, testing, and documentation.
Experience working with large-scale and complex enterprise datasets.
Strong understanding of Guidewire InsuranceSuite, Guidewire data models, or Guidewire-based data integrations.
Experience working with insurance domain data such as Policy, Claims, Billing, Customer, Producer, and Underwriting data.
Strong problem-solving, communication, stakeholder management, and technical leadership skills.

Guidewire-Specific Requirements

Experience integrating data from Guidewire applications into enterprise data platforms.
Strong understanding of Guidewire data structures and insurance business processes.
Experience with Guidewire PolicyCenter, ClaimCenter, and/or BillingCenter data is highly preferred.
Ability to work with Guidewire APIs, extracts, events, or integration mechanisms where applicable.
Experience in designing downstream data pipelines and analytics solutions for Guidewire-generated data.
Understanding of insurance data governance, reconciliation, and data quality requirements.

Good-to-Have Skills

Experience with Azure Synapse Analytics.
Experience with Azure Functions.
Knowledge of Python and/or PySpark for custom data transformations and engineering solutions.
Experience with Databricks is an added advantage.
Experience with legacy technologies such as DataStage or Netezza.
Strong understanding of CI/CD pipelines and DevOps practices for data workflows.
Experience with data governance, metadata management, data catalog, and data lineage tools.
Exposure to Power BI, Tableau, or other BI and analytics tools.
Experience in insurance industry data modernization and cloud migration projects.

Qualifications

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
8+ years of experience in Data Engineering with strong exposure to Azure and cloud data platforms.
Demonstrated experience leading data engineering teams or providing technical leadership on enterprise data projects.
Strong understanding of modern cloud data architecture, ETL/ELT, data warehousing, and data governance.
Excellent communication and collaboration skills with the ability to work across business and technical teams.