Data Engineer
We’re on a mission to change the future of clinical research. At Perceptive, we help the
biopharmaceutical industry bring medical treatments to the market, faster.
Our mission is to change the world but to do this, we need people like you.
As Data Engineer, Medical Imaging, you will support the design, development, and maintenance of scalable, secure, and compliant data solutions that enable analytics, reporting, and AI/ML workloads.
You will contribute to data ingestion, transformation, modelling, and orchestration activities, enabling reliable and high-quality data across the organisation with appropriate guidance.
In this role, you will work as part of a team building modern cloud data platforms, supporting data operations, and ensuring performance, reliability and compliance with industry standards.
Key Responsibilities
Cloud-Native Data Architecture & Pipeline Engineering
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Build scalable, cloud-native data pipelines for batch and streaming workloads
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Support the implementation of data ingestion frameworks for structured, semi-structured, and unstructured data
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Develop APIs and integration services for data exchange between internal systems
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Collaborating with Senior Engineers, support platform scalability and reliability across global operations
Data Modelling & Storage Design
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Support the implementation of database and storage solutions across relational, NoSQL, and data lake systems.
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Develop metadata-driven ingestion and transformation frameworks
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Assist in ensuring data schemas support analytics, AI/ML, and business applications
Data Transformation, Quality & Governance
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Implement data quality frameworks, validation rules, and automated checks
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Build reusable transformation components to standardise data processing
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Support the implementation of data lineage, cataloguing, and governance capabilities under guidance
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Following established policies, ensure data privacy, protection, and compliance with regulatory requirements
Data Platform Development & Optimization
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Develop high-throughput data processing solutions using distributed systems
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Assist in optimising data pipelines for performance, cost efficiency, and resilience
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Contribute to observability and monitoring activities for pipeline health, data drift, and SLA compliance
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Build caching, partitioning, and indexing strategies to improve query performance
Analytics & AI/ML Enablement
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Support the enablement of data scientists with curated datasets and feature pipelines
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Develop real-time or batch-oriented feature stores
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Integrate data workflows with ML operations (MLOps) and model deployment systems under guidance
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Build visualisation-ready datasets for BI tools and dashboards
Security, Compliance & Risk Management
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Apply established security practices to implement role-based access control, encryption, and secure data-sharing patterns
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Support compliance with FDA/GxP, GDPR, HIPAA, and other applicable regulations
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Develop audit trails, data retention, and disaster recovery solutions
Innovation
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Stay informed on emerging data engineering, AI, and cloud technologies, developing technical capability and experience across data engineering domains
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Share insights and drive continuous improvement across data engineering practices
Functional Competencies (Technical knowledge/Skills)
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Working knowledge of cloud-native data platforms and serverless architectures (Azure, AWS)
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Good understanding of CI/CD and DevOps concepts
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Understanding of data modelling concepts
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Familiarity with API patterns
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Knowledge of streaming platforms (Kafka, Kinesis, Pub/Sub, Event Hubs)
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Strong SQL skills
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Good communication skills with ability to work across technical and business teams
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Demonstrates willingness to learn and develop technical skills
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A flexible attitude with respect to work assignments and new learning.
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Ability to manage multiple and varied tasks with enthusiasm and prioritize workload with attention to detail.
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Ability to identify and implement process improvements.
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Proactively participates in skills improvement training and encourages their teams to participate.
Experience, Education and Certifications
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Experience in data pipeline orchestration (e.g., Airflow, Prefect, Dagster).
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Experience with scalable data processing frameworks (Spark, Flink, Beam, Databricks).
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Experience working in data engineering or related technical roles.
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Exposure to cloud-native data platforms (Azure, AWS, or GCP).
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Exposure to modern ELT/ETL tools and distributed data processing.
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Good experience in Python, SQL, and optionally 3GL technologies.
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Exposure to modern data warehousing and lakehouse platforms.
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Exposure to analytics tools (Power BI, Tableau, Looker) beneficial.
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Bachelor's Degree in Computer Science, Data Engineering, Software Engineering, or related discipline.
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English: Fluent.
Salary Range
- This position attracts a salary of up to EUR 47,300 per year.