Life Sciences Data Engineer, Insights & Analytics

Cph Ai Hub; København; Ibrido; DKK 550.000 - 900.000; Tempo pieno

Vantaggi offerti da questo lavoro

Flexible working

Learning opportunities

Wellbeing support

Descrizione del lavoro

BASE life science is seeking a Data Engineer to design, develop, automate, and maintain robust data pipelines for analytics in the life sciences sector. You will collaborate with analysts and domain experts to ensure data architecture supports BI across pharmaceutical projects.

You will leverage Azure Databricks, Azure Data Factory, PySpark and Python, while ensuring data quality, lineage, and end-to-end test coverage in a dynamic consulting environment.

Competenze

• Bachelor’s or Master’s degree in computer science, data engineering, information systems or related field.
• At least 2 years hands-on experience as a Data Engineer on medium to complex projects, preferably in life sciences.
• At least 2 years hands-on experience with cloud data transformation platforms (Azure Databricks, AWS or GCP) and Python.
• Proficiency in SQL and relational databases; experience with Azure data services and Databricks is expected.

Mansioni

• Build, implement, and automate data ingestion pipelines from diverse sources with transformations.
• Develop and maintain data processing solutions using Azure Databricks, Azure Data Factory, SQL, Python and PySpark.
• Apply data quality practices to ensure high-quality, reliable data for downstream systems.
• Add error handling, monitoring, auditing, and data lineage for end-to-end traceability.
• Design end-to-end tests to validate data flows and ensure accurate data from source to target.
• Collaborate with cross-functional teams including data privacy, business analysts and QA.

Conoscenze

Python

SQL

Data engineering

Problem solving

Formazione

Bachelor's or Master's in Computer Science or related field

Strumenti

Azure Databricks

Azure Data Factory

Delta Lake

Power BI

Tableau

Qlik

Descrizione del lavoro

BASE life science is seeking a Data Engineer to design, develop, automate, and maintain robust data pipelines for analytics in the life sciences sector. You will collaborate with analysts and domain experts to ensure data architecture supports BI across pharmaceutical projects.

You will leverage Azure Databricks, Azure Data Factory, PySpark and Python, while ensuring data quality, lineage, and end-to-end test coverage in a dynamic consulting environment.