Data engineer in life sciences

Drive meaningful impact across the life sciences industry. As our next Data Engineer – Data Insights & Analytics you will contribute to solving meaningful challenges across the life sciences industry. We offer specialised management consulting services, working with top-tier life sciences companies as well as biotech startups — locally and globally. From strategy development to hands-on implementation, we support our clients were impact matters most. About the role We seek a skilled and motivated Data Engineer to join our Data Insights & Analytics team. In this role, you will be responsible for designing, developing, automating, and maintaining robust data pipelines to ensure efficient data collection, storage, transformation, and processing.

• Build, implement, and automate efficient data ingestion pipelines that integrate data from diverse sources, including structured, semi-structured, and unstructured formats, while applying necessary business logic and transformations.
• Develop and maintain data processing solutions using technologies such as Azure Databricks, Azure Data Factory, SQL, Python, and PySpark.
• Apply data quality practices and frameworks to minimize anomalies and ensure the production of high-quality, reliable data for downstream systems.
• Incorporate error handling, exception management, monitoring, and auditing mechanisms to maintain end-to-end data traceability and support data lineage.
• Design and execute end-to-end tests to ensure the data pipeline and solutions are functioning as expected, covering a variety of data scenarios and ensuring that data flows accurately and reliably from source to target.
• Work closely with cross-functional teams, including data privacy officers, business analysts, and quality assurance teams, to ensure alignment with organizational goals and to facilitate seamless data integration and usage.

• Educational background: 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, with a focus on medium to complex data engineering projects, preferably in the pharmaceutical domain.
• Minimum of 2 years of hands-on experience in 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 is a must.
• Proficient in Structured Query Language (SQL) and experienced in working with relational databases and cloud-based data platforms.
• Experience with Microsoft Azure data services and Databricks, including technologies such as 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.
• Good understanding of Veeva, Salesforce, IQVIA data models and data sources across HR and Sales functions.
• Familiarity with data visualization and analytics tools such as Power BI, Tableau, and Qlik is essential.
• Strong consulting mindset with the ability to work independently on defined tasks and collaborate effectively within medium to large-scale project teams.
• Proven ability to work in dynamic, fast-paced project environments without compromising on quality.
• Excellent problem-solving and troubleshooting abilities.
• Будет плюсом: relevant certifications are a plus; Familiarity with RESTful APIs, Git, DevOps practices, and CI/CD processes is a plus

• At BASE, you work on meaningful, complex challenges at the intersection of technology, science, and business.
• We trust our people with real responsibility and support them in turning ambition into impact — grounded in five core values: team spirit, trust, openness, ambition, and execution.
• Ambition, encouraged through ownership and continuous learning.
• Execution — we focus on delivering solutions that work in practice.
• Openness — your ideas are heard, challenged constructively, and supported as you grow.
• Flexible ways of working, built on trust, autonomy, and balance.
• The opportunity to shape a practice, not just staff one.
• Support for health and wellbeing, covering physical, mental, and social needs
• 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
• The opportunity to work on challenges that make a meaningful difference for patients and healthcare systems worldwide