Data Engineer – DInA

BASE life science

. Design, develop, automate, and maintain robust data pipelines .

Posted 10/2/2026full-timeCopenhagen • DenmarkJuniorMid-LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining data pipelines using Azure Databricks, SQL, and Python, with a strong focus on data quality and transformation practices. Proven ability to collaborate with cross-functional teams in the pharmaceutical domain to deliver reliable data solutions.

Highest-signal resume keywords

Azure DatabricksData Pipeline DevelopmentSQL ProficiencyPython ScriptingData Quality Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data IngestionETL/ELT ProcessesData ModelingIncremental ProcessingData TransformationRelational DatabasesData ArchitectureDimensional ModelingData LineageEnd-to-End Testing

Soft Skills

Problem-SolvingCollaborationConsulting MindsetIndependenceAdaptability

Tools & Technologies

Azure Data FactoryAzure Data Lake StorageDelta LakePower BITableauQlikGitDevOps PracticesCI/CD ProcessesRESTful APIs

Industry Keywords

Pharmaceutical DomainData PrivacyQuality AssuranceLife SciencesVeevaSalesforceIQVIA

Tech Stack

Tools & technologies

AWSAzureCloudETLGoogle Cloud PlatformPySparkPythonSQLTableau

About the role

Key responsibilities & impact

Design, develop, automate, and maintain robust data pipelines
Build, implement, and automate data ingestion pipelines integrating structured, semi-structured, and unstructured data sources
Apply business logic and transformations to ingested data
Develop and maintain data processing solutions using Azure Databricks, Azure Data Factory, SQL, Python, and PySpark
Apply data quality practices and frameworks to minimize anomalies and produce reliable downstream data
Implement error handling, exception management, monitoring, and auditing mechanisms
Maintain end-to-end data traceability and support data lineage
Design and execute end-to-end tests across varied data scenarios
Ensure accurate and reliable data flow from source to target
Collaborate with data privacy officers, business analysts, quality assurance teams, cross-functional teams, and pharmaceutical domain experts
Support data architecture for advanced analytics and business intelligence across pharmaceutical projects
Contribute to meaningful consulting and technology solutions for life sciences clients

Requirements

What you’ll need

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field
Minimum of 2 years of hands-on experience in a Data Engineer role, preferably in the pharmaceutical domain
Minimum of 2 years of hands-on experience with cloud data transformation platforms such as Azure Databricks, AWS, or GCP
Minimum of 2 years of hands-on experience in Python or equivalent scripting languages
Proficiency in SQL and experience with relational databases and cloud-based data platforms
Experience with Microsoft Azure data services and Databricks, including Azure Data Factory, Azure Data Lake Storage, Delta Lake, Python, and PySpark
Experience with ETL/ELT processes, data ingestion, transformation, incremental processing, and data quality practices
Experience in data modeling and layered data architectures, including Medallion architecture and dimensional modeling concepts
Familiarity with RESTful APIs, Git, DevOps practices, and CI/CD processes is a plus
Good understanding of Veeva, Salesforce, and IQVIA data models and data sources across HR and Sales functions
Familiarity with Power BI, Tableau, and Qlik is essential
Strong consulting mindset and ability to work independently and collaborate within medium to large-scale project teams
Ability to work in dynamic, fast-paced project environments without compromising quality
Excellent problem-solving and troubleshooting abilities
Application must be submitted in English

Benefits

Comp & perks

Support for health and wellbeing, covering physical, mental, and social needs
Flexible ways of working, built on trust, autonomy, and balance
Ongoing learning and professional development throughout your career
A modern work setup, with the tools and equipment needed to do great work
Recognition of performance and impact, linked to contribution and results
Opportunity to work on challenges that make a meaningful difference for patients and healthcare systems worldwide
Continuous learning and ownership opportunities
Diverse and inclusive workplace
Application and recruitment process in English