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.
- Apart from job satisfaction, we can offer you: HEALTH:
- Medical plan for you and your dependents.
- Personal Accident Insurance
- Life Insurance
- Critical illness cover
- Salary structure and Flexi basket
- Provident fund of 12%
- Gratuity scheme
As a Senior Data Engineer, Medical Imaging you will design, build, and optimize scalable, secure, and compliant data platforms that support advanced analytics, operational reporting, and AI/ML workloads. You will specialise in data ingestion, transformation, modelling, and orchestration, enabling high quality data flows across the organisation. In this role, you will contribute to modern cloud data architectures, metadata management, and real time/streaming data operations. Your expertise will drive innovation in data engineering capabilities while ensuring performance, reliability, and regulatory compliance.
Key Responsibilities
Cloud-Native Data Architecture & Pipeline Engineering
- Build scalable, cloud-native data pipelines for batch and streaming workloads.
- Design ELT/ETL workflows using modern orchestration tools.
- Implement data ingestion frameworks for structured, semi-structured, and unstructured data.
- Develop APIs and integration services for data exchange between internal systems.
- Support platform scalability and reliability across global operations.
Data Modelling & Storage Design
- Design high‑performance data models including dimensional, canonical, and domain-driven structures.
- Implement database and storage solutions across relational, NoSQL, and data lake systems.
- Develop metadata-driven ingestion and transformation frameworks.
- Ensure data schemas support analytics, AI/ML, and business applications.
Data Transformation, Quality & Governance
- Implement data quality frameworks, validation rules, and automated checks.
- Build reusable transformation components to standardise data processing.
- Implement data lineage, cataloguing, and governance capabilities.
- Ensure data privacy, protection, and compliance with regulatory requirements.
Data Platform Development & Optimization
- Develop high-throughput data processing solutions using distributed systems.
- Optimize data pipelines for performance, cost efficiency, and resilience.
- Implement observability and monitoring for pipeline health, data drift, and SLA compliance.
- Build caching, partitioning, and indexing strategies to improve query performance.
Analytics & AI/ML Enablement
- Enable data scientists with curated datasets and feature pipelines.
- Develop real-time or batch-oriented feature stores.
- Integrate data workflows with ML operations (MLOps) and model deployment systems.
- Build visualisation-ready datasets for BI tools and dashboards.
Security, Compliance & Risk Management
- Implement role-based access control, encryption, and secure data-sharing patterns.
- Support compliance with FDA/GxP, GDPR, HIPAA, and other applicable regulations.
- Develop audit trails, data retention, and disaster recovery solutions.
Technical Leadership & Collaboration
- Contribute to technology stack decisions for data engineering and analytics workloads.
- Participate in code reviews and enforce engineering best practices.
- Collaborate in architecture reviews and system design decisions.
- Mentor junior engineers and share knowledge across teams.
Innovation
- Stay current with emerging data engineering, AI, and cloud technologies.
- Evaluate new tools and frameworks to improve platform capabilities.
- Share insights and drive continuous improvement across data engineering practices.
Other
- Carryout any other reasonable duties as requested.
Functional Competencies (Technical knowledge/Skills)
- Strong knowledge of cloud-native data platforms and serverless architectures (Azure, AWS)
- Expertise in data pipeline orchestration (e.g., Airflow, Prefect, Dagster)
- Strong knowledge of data modelling in Python
- Familiarity with API development in .Net/Java
- Knowledge of streaming platforms (Kafka, Kinesis, Pub/Sub, Event Hubs)
- Strong SQL and data modelling capabilities
- Experience with scalable data processing frameworks (Spark, Flink, Beam, Databricks)
- Understanding of healthcare or clinical trial data workflows (preferred)
- Knowledge of data governance, metadata management, and lineage frameworks
- Strong communication skills with ability to work across technical and business teams
- Ability to balance technical solutions with business objectives.
Behaviour Competencies
- Accountability
- Adaptability
- Customer focus
- Robust
- Decision Making
- Business Acumen
- Results orientation
- Time Management
- Willingness to learn
- Team collaboration
Experience, Education and Certifications
- Significant experience delivering large-scale data engineering solutions.
- Experience developing cloud-native data platforms (Azure, AWS, or GCP).
- Experience with modern ELT/ETL tools and distributed data processing.
- Experience working in regulated industries (healthcare, clinical trials, finance) preferred.
- Proficiency in Python, SQL, and optionally Java/Scala.
- Experience with CI/CD pipelines and DevOps for data workflows.
- Experience with modern data warehousing and lakehouse platforms.
- Experience with analytics tools (Power BI, Tableau, Looker) beneficial.
- Bachelor's Degree in Computer Science, Data Engineering, Software Engineering, or related discipline.
- Advanced degrees or cloud certifications preferred.
- English: Fluent.
Come as you are.
We're proud to be a Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
