Seeking a contracted Data Engineer to support the design development and maintenance of data pipelines and analytics infrastructure powering commercial and medical insights. The successful candidate will work across Microsoft Fabric Power BI and emerging AI integration platforms to deliver scalable governed data solutions. This role requires strong hands-on ETL development skills comfort working in a regulated pharmaceutical environment and the ability to bridge technical data engineering work with business analytics needs.
Key Responsibilities
Data pipeline development: Design build and maintain ETL/ELT pipelines using Microsoft Fabric (Data Factory Dataflows Gen2 Lakehouses) to ingest transform and serve data from internal and external sources.
Power BI analytics: Develop and optimize Power BI semantic models DAX measures and reports supporting commercial analytics (e.g. sales dashboards HCP engagement tracking inventory monitoring).
AI data integration: Build and maintain MCP (Model Context Protocol) server integrations to connect enterprise data sources with AI solutions such as Copilot and Claude enabling AI-assisted analytics and decision support.
Data governance: Support data quality lineage documentation and compliance with data governance standards including data inventory and validation requirements.
Cross-functional collaboration: Work closely with business stakeholders IT teams and global data platform teams to translate data requirements into technical solutions and ensure alignment with enterprise architecture.
Requirements
Required Qualifications
Experience: 35 years of hands-on data engineering experience including ETL pipeline development data modeling and analytics platform support.
Technical skills: Proficiency in Microsoft Fabric (Data Factory Dataflows Gen2 Lakehouse SQL Analytics Endpoint) Power BI (semantic models DAX Power Query M) and SQL. Experience with Python for data transformation is a plus.
AI integration: Demonstrated experience or strong familiarity with MCP server architecture and integrating structured data sources with AI platforms (e.g. Copilot Claude or similar LLM-based tools).
Domain background: Prior experience in the pharmaceutical or healthcare industry preferred; familiarity with commercial data (sales HCP consent) is an advantage.
Language: Native Korean speaker with fluent English (business-level written and verbal communication required).
Location: Prefer to work on-site.
What We Are Looking For
Problem solver: Approaches data challenges methodically identifies root causes in pipeline failures and implements durable fixes.
Self-directed: Takes ownership of deliverables and proactively identifies data quality issues or optimization opportunities without waiting for direction.
Collaborative communicator: Translates complex technical concepts into clear language for business stakeholders and works effectively across bilingual (EN/KR) teams.
Continuous learner: Stays current with evolving data platform capabilities (e.g. Fabric updates AI tooling advancements) and applies new techniques to improve existing solutions.
Required Skills:
About the Role
Seeking a contracted Data Engineer to support the design development and maintenance of data pipelines and analytics infrastructure powering commercial and medical insights. The successful candidate will work across Microsoft Fabric Power BI and emerging AI integration platforms to deliver scalable governed data solutions. This role requires strong hands-on ETL development skills comfort working in a regulated pharmaceutical environment and the ability to bridge technical data engineering work with business analytics needs.
Key Responsibilities
Data pipeline development: Design build and maintain ETL/ELT pipelines using Microsoft Fabric (Data Factory Dataflows Gen2 Lakehouses) to ingest transform and serve data from internal and external sources.
Power BI analytics: Develop and optimize Power BI semantic models DAX measures and reports supporting commercial analytics (e.g. sales dashboards HCP engagement tracking inventory monitoring).
AI data integration: Build and maintain MCP (Model Context Protocol) server integrations to connect enterprise data sources with AI solutions such as Copilot and Claude enabling AI-assisted analytics and decision support.
Data governance: Support data quality lineage documentation and compliance with data governance standards including data inventory and validation requirements.
Cross-functional collaboration: Work closely with business stakeholders IT teams and global data platform teams to translate data requirements into technical solutions and ensure alignment with enterprise architecture.
Requirements
Required Qualifications
Experience: 35 years of hands-on data engineering experience including ETL pipeline development data modeling and analytics platform support.
Technical skills: Proficiency in Microsoft Fabric (Data Factory Dataflows Gen2 Lakehouse SQL Analytics Endpoint) Power BI (semantic models DAX Power Query M) and SQL. Experience with Python for data transformation is a plus.
AI integration: Demonstrated experience or strong familiarity with MCP server architecture and integrating structured data sources with AI platforms (e.g. Copilot Claude or similar LLM-based tools).
Domain background: Prior experience in the pharmaceutical or healthcare industry preferred; familiarity with commercial data (sales HCP consent) is an advantage.
Language: Native Korean speaker with fluent English (business-level written and verbal communication required).
Location: Prefer to work on-site.
What We Are Looking For
Problem solver: Approaches data challenges methodically identifies root causes in pipeline failures and implements durable fixes.
Self-directed: Takes ownership of deliverables and proactively identifies data quality issues or optimization opportunities without waiting for direction.
Collaborative communicator: Translates complex technical concepts into clear language for business stakeholders and works effectively across bilingual (EN/KR) teams.
Continuous learner: Stays current with evolving data platform capabilities (e.g. Fabric updates AI tooling advancements) and applies new techniques to improve existing solutions.
About the RoleSeeking a contracted Data Engineer to support the design development and maintenance of data pipelines and analytics infrastructure powering commercial and medical insights. The successful candidate will work across Microsoft Fabric Power BI and emerging AI integration platforms to del...
About the Role
Seeking a contracted Data Engineer to support the design development and maintenance of data pipelines and analytics infrastructure powering commercial and medical insights. The successful candidate will work across Microsoft Fabric Power BI and emerging AI integration platforms to deliver scalable governed data solutions. This role requires strong hands-on ETL development skills comfort working in a regulated pharmaceutical environment and the ability to bridge technical data engineering work with business analytics needs.
Key Responsibilities
Data pipeline development: Design build and maintain ETL/ELT pipelines using Microsoft Fabric (Data Factory Dataflows Gen2 Lakehouses) to ingest transform and serve data from internal and external sources.
Power BI analytics: Develop and optimize Power BI semantic models DAX measures and reports supporting commercial analytics (e.g. sales dashboards HCP engagement tracking inventory monitoring).
AI data integration: Build and maintain MCP (Model Context Protocol) server integrations to connect enterprise data sources with AI solutions such as Copilot and Claude enabling AI-assisted analytics and decision support.
Data governance: Support data quality lineage documentation and compliance with data governance standards including data inventory and validation requirements.
Cross-functional collaboration: Work closely with business stakeholders IT teams and global data platform teams to translate data requirements into technical solutions and ensure alignment with enterprise architecture.
Requirements
Required Qualifications
Experience: 35 years of hands-on data engineering experience including ETL pipeline development data modeling and analytics platform support.
Technical skills: Proficiency in Microsoft Fabric (Data Factory Dataflows Gen2 Lakehouse SQL Analytics Endpoint) Power BI (semantic models DAX Power Query M) and SQL. Experience with Python for data transformation is a plus.
AI integration: Demonstrated experience or strong familiarity with MCP server architecture and integrating structured data sources with AI platforms (e.g. Copilot Claude or similar LLM-based tools).
Domain background: Prior experience in the pharmaceutical or healthcare industry preferred; familiarity with commercial data (sales HCP consent) is an advantage.
Language: Native Korean speaker with fluent English (business-level written and verbal communication required).
Location: Prefer to work on-site.
What We Are Looking For
Problem solver: Approaches data challenges methodically identifies root causes in pipeline failures and implements durable fixes.
Self-directed: Takes ownership of deliverables and proactively identifies data quality issues or optimization opportunities without waiting for direction.
Collaborative communicator: Translates complex technical concepts into clear language for business stakeholders and works effectively across bilingual (EN/KR) teams.
Continuous learner: Stays current with evolving data platform capabilities (e.g. Fabric updates AI tooling advancements) and applies new techniques to improve existing solutions.
Required Skills:
About the Role
Seeking a contracted Data Engineer to support the design development and maintenance of data pipelines and analytics infrastructure powering commercial and medical insights. The successful candidate will work across Microsoft Fabric Power BI and emerging AI integration platforms to deliver scalable governed data solutions. This role requires strong hands-on ETL development skills comfort working in a regulated pharmaceutical environment and the ability to bridge technical data engineering work with business analytics needs.
Key Responsibilities
Data pipeline development: Design build and maintain ETL/ELT pipelines using Microsoft Fabric (Data Factory Dataflows Gen2 Lakehouses) to ingest transform and serve data from internal and external sources.
Power BI analytics: Develop and optimize Power BI semantic models DAX measures and reports supporting commercial analytics (e.g. sales dashboards HCP engagement tracking inventory monitoring).
AI data integration: Build and maintain MCP (Model Context Protocol) server integrations to connect enterprise data sources with AI solutions such as Copilot and Claude enabling AI-assisted analytics and decision support.
Data governance: Support data quality lineage documentation and compliance with data governance standards including data inventory and validation requirements.
Cross-functional collaboration: Work closely with business stakeholders IT teams and global data platform teams to translate data requirements into technical solutions and ensure alignment with enterprise architecture.
Requirements
Required Qualifications
Experience: 35 years of hands-on data engineering experience including ETL pipeline development data modeling and analytics platform support.
Technical skills: Proficiency in Microsoft Fabric (Data Factory Dataflows Gen2 Lakehouse SQL Analytics Endpoint) Power BI (semantic models DAX Power Query M) and SQL. Experience with Python for data transformation is a plus.
AI integration: Demonstrated experience or strong familiarity with MCP server architecture and integrating structured data sources with AI platforms (e.g. Copilot Claude or similar LLM-based tools).
Domain background: Prior experience in the pharmaceutical or healthcare industry preferred; familiarity with commercial data (sales HCP consent) is an advantage.
Language: Native Korean speaker with fluent English (business-level written and verbal communication required).
Location: Prefer to work on-site.
What We Are Looking For
Problem solver: Approaches data challenges methodically identifies root causes in pipeline failures and implements durable fixes.
Self-directed: Takes ownership of deliverables and proactively identifies data quality issues or optimization opportunities without waiting for direction.
Collaborative communicator: Translates complex technical concepts into clear language for business stakeholders and works effectively across bilingual (EN/KR) teams.
Continuous learner: Stays current with evolving data platform capabilities (e.g. Fabric updates AI tooling advancements) and applies new techniques to improve existing solutions.
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