Data Engineer, Quality Data Warehouse

Greetings from Orcapod consulting services

We have the openings for

Data Engineer, Quality Data Warehouse

Experience

5 to 8 Years

Role Overview

We are looking for a hands-on Data Engineer to support the design, development, and enhancement of a Quality Data Warehouse for a Pharma/Life Sciences customer.

The solution supports Quality and GxP-related analytics and reporting, including APQR, inspection, audit, training-compliance, and quality-data use cases. The environment includes established quality data products and reporting assets that are enhanced incrementally based on evolving Quality and compliance needs.

The candidate will work as part of a 79 member cross-functional team comprising Data Engineers, Business Analysts, Test/Quality Engineers, and Project Management.

Key Responsibilities

• Design, build, and enhance enterprise Quality Data Warehouse solutions.
• Develop and maintain scalable data pipelines using Snowflake, dbt, and Matillion.
• Build and extend data models supporting:
• Quality analytics
• APQR reporting
• Audit and inspection reporting
• Training compliance
• Quality KPIs and compliance indicators
• Work with existing Data Vault architecture and reusable quality-focused data models.
• Build ingestion pipelines from enterprise source systems, including:
• Veeva
• Oracle-based sources
• Other quality-relevant enterprise systems
• Perform source-to-target mapping and transformation development.
• Implement data-validation, reconciliation, and data-quality controls.
• Ensure traceability between source data, transformation logic, and reporting outputs.
• Support historical data loads, incremental processing, reprocessing, and production fixes.
• Collaborate with Quality stakeholders, BAs, platform teams, and testers.
• Investigate upstream data-quality and consistency issues that may affect Quality reporting.
• Support deployment and release activities within a GxP-controlled environment.
• Maintain technical documentation required for validated solutions.
• Participate in defect resolution, root-cause analysis, and production support.
• Follow established engineering, security, governance, and change-management standards.

Mandatory Skills

• Strong hands-on experience with Snowflake
• Strong experience with dbt
• Strong SQL skills
• ETL/ELT and enterprise data-warehouse experience
• Dimensional and relational data modeling
• Experience designing complex enterprise data pipelines
• Data quality and reconciliation
• Source-to-target mapping
• Strong debugging and troubleshooting skills
• Experience working in structured Agile delivery environments

Preferred Skills

• Matillion
• Power BI data-model understanding
• Data Vault / Data Vault 2.0
• Veeva data
• Oracle data sources
• Python
• Pharma / Life Sciences experience
• Quality-domain data experience
• GxP / validated-system experience

GxP Expectations

The candidate should understand that changes to a validated data solution require strong discipline around:

• Requirements traceability
• Controlled changes
• Test evidence
• Data integrity
• Documentation
• Auditability
• Defect management
• Release controls

The role does not own Quality processes or final validation sign-off, but must provide the technical implementation and evidence required to support GxP-aligned delivery. The source white paper specifically separates data-delivery responsibilities from Quality-system ownership and validation sign-off.

Ideal Candidate

A strong Data Engineer who combines Snowflake, dbt, enterprise data warehousing, and data modeling expertise with the rigor required to deliver reliable and traceable data products in a regulated Pharma environment.

If interested please share your profile to [email protected]

Regards .

Roopa