Senior Data Engineer
1 day ago
When our values align, there's no limit to what we can achieve.
At Parexel, we all share the same goal - to improve the world's health. From clinical trials to regulatory, consulting, and market access, every clinical development solution we provide is underpinned by something special - a deep conviction in what we do.
Each of us, no matter what we do at Parexel, contributes to the development of a therapy that ultimately will benefit a patient. We take our work personally, we do it with empathy and we're committed to making a difference.
- Architect, implement, and optimize ETL/ELT workflows using tools such as Databricks and Informatica to ingest and process large datasets.
- Deploy and manage data infrastructure on Azure and AWS, including containerized services and serverless components.
- Partner with data scientists, software engineers, and business stakeholders to translate requirements into scalable data solutions.
- Monitor and tune pipeline performance, implement robust monitoring/alerting (e.g., Prometheus, DataDog), and troubleshoot production issues.
- Define and enforce data validation rules, lineage tracking, and governance standards to ensure accurate and compliant data usage.
- Build CI/CD pipelines for data code, automate deployments, and support model operationalization workflows.
- Share knowledge of data engineering best practices, conduct code reviews, and mentor junior engineers.
Qualification:
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field.
- 8+ years of hands-on experience designing and building data pipelines and infrastructure.
- Strong proficiency in data engineering tools and technologies, such as Apache Spark, Hadoop, Kafka, and cloud-based platforms (AWS, Azure, or GCP).
- Hands-on experience with data modeling, ETL processes, and distributed data processing frameworks.
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