Data Engineer designing and maintaining scalable data solutions on Databricks for clinical trials. Collaborating with teams to overcome data challenges and ensure the smooth logistics of clinical supplies.
About the role
- Staff Data Engineer at PayPal designing and implementing data systems to support business needs. Leading data engineering projects and mentoring junior engineers while ensuring data quality and integrity.
Responsibilities
- Lead and manage data engineering projects, ensuring timely delivery and alignment with business goals.
- Develop and maintain data architectures and pipelines to support data analysis and decision-making.
- Analyze complex datasets to identify trends, patterns, and insights that drive strategic initiatives.
- Collaborate with cross-functional teams to understand data needs and provide actionable insights.
- Ensure data quality and integrity through regular audits and validation processes.
- Mentor and guide junior data engineers, fostering a culture of continuous learning and improvement.
- Architect and hands-on develop enterprise-class data platforms capable of processing billions of records with high reliability and performance.
- Write and optimize advanced complex SQL for data transformation, analysis, and performance tuning at petabyte scale.
- Drive innovation through Agentic AI - conceptualize and design data solutions that leverage Agentic AI capabilities.
Requirements
- 5+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience
- 8+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience
- Strong collaboration skills and ability to influence across teams through technical credibility
- Excellent debugging and troubleshooting skills for complex distributed data systems
- Demonstrated deep hands-on mastery building enterprise-class data platforms and pipelines at massive scale
- Expert-level SQL skills - proven ability to write, optimize, and troubleshoot complex queries across billions of records
- Extensive experience with both batch processing (Spark, Dataproc) and real-time/streaming systems (Kafka, Pub/Sub, Dataflow)
- Strong Python programming skills with focus on performance and scalability
- Experience with workflow orchestration at scale (Airflow, UC4, or similar)
- Strong understanding of data modeling, schema design, data warehouse architecture, and data lake patterns
- Experience with CI/CD pipelines, infrastructure as code, and DevOps practices
- Experience with Agentic AI and conceptualize innovative data solutions with outside-the-box thinking
- Experience building Customer Data Platforms (CDP) and Customer Segmentation and Activation across owned and paid channels
- Experience with real-time integration with third-party AdTech platforms and Attribution and Analytics systems
- Experience with AI/ML pipelines or AI-enhanced data systems.
Benefits
- Generous paid time off
- Healthcare coverage for you and your family
- Resources to create financial security and support your mental health
- Flexible, balanced work culture
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