Senior Specialist , Data Engineering

Senior Specialist, Data Engineering

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.