Based in Singapore, join a global healthcare biopharma company and be part of a 130- year legacy of success backed by ethical integrity, forward momentum, and an inspiring mission to achieve new milestones in global healthcare.
What will you do in this role:
- Design, develop, and maintain data pipelines to extract data from various sources and populate a data lake and data warehouse.
- Work closely with data scientists, analysts, and business teams to understand data requirements and deliver solutions aligned with business goals.
- Build and maintain platforms that support data ingestion, transformation, and orchestration across various data sources, both internal and external.
- Use data orchestration, logging, and monitoring tools to build resilient pipelines.
- Automate data flows and pipeline monitoring to ensure scalability, performance, and resilience of the platform.
- Monitor, troubleshoot, and resolve issues related to the data integration platform, ensuring uptime and reliability.
- Maintain thorough documentation for integration processes, configurations, and code to ensure easy onboarding for new team members and future scalability.
- Develop pipelines to ingest data into cloud data warehouses.
- Establish, modify and maintain data structures and associated components.
- Create and deliver standard reports in accordance with stakeholder needs and conforming to agreed standards.
- Work within a matrix organizational structure, reporting to both the functional manager and the project manager.
- Participate in project planning, execution, and delivery, ensuring alignment with both functional and project goals.
What should you have :
- Bachelors degree in Information Technology, Computer Science or any Technology stream.
- 10+ years of developing data pipelines & data infrastructure, ideally within a drug development or life sciences context.
- Demonstrated expertise in delivering large-scale information management technology solutions encompassing data integration and self-service analytics enablement.
- Experienced in software/data engineering practices (including versioning, release management, deployment of datasets, agile & related software tools).
- Ability to design, build and unit test applications on Spark framework on Python.
- Build PySpark based applications for both batch and streaming requirements, which will require in-depth knowledge on Databricks/ Hadoop.
- Experience working with storage frameworks like Delta Lake/ Iceberg
- Experience working with MPP Datawarehouse's like Redshift
- Cloud-native, ideally AWS certified.
- Strong working knowledge of at least one Reporting/Insight generation technology
- Good interpersonal and communication skills (verbal and written).
- Proven record of delivering high-quality results.
- Product and customer-centric approach.
- Innovative thinking, experimental mindset.
