- Work model
- Remote
- Experience
- 5+ years
- Employment
- Not specified
- Compensation
- Not disclosed
- Technology signal
- 20 tags
Technology context
20Parsed from the vacancy text; ordered by relevance to this role.
AIAWSMachine LearningPythonCloud NativeCloudMicroservicesAPISnowflakeRESTCI/CDSQLAirflowGitScrumData IntegrationDatadogdbtGitHub ActionsMonte Carlo Data
Full listing
Role description
We are looking for a Senior/Lead Data Engineer to design, build and maintain data products, pipelines and transversal capabilities that support decision-making across a global pharma organization.
Responsibilities
- Design, develop and maintain a production-grade data platform with data observability capabilities
- Build and optimize scalable data pipelines and ETL/ELT workflows
- Develop and deploy cloud-native solutions on AWS
- Implement and maintain CI/CD pipelines
- Conduct code reviews and enforce coding standards and testing practices
- Collaborate with data scientists, ML engineers and product managers to deliver technical solutions
- Contribute to architecture discussions and design decisions
- Participate in Agile/Scrum ceremonies
Requirements
- 8+ years of professional data engineering experience with data infrastructure and data platform expertise
- Proficiency in SQL and Python to write clean, efficient, well-tested code
- Proven track record of designing, building and deploying complex data platforms and data products
- Expertise in Airflow, DBT and Snowflake along with AWS native services
- Familiarity with data observability tools such as Datadog and Monte Carlo
- Skills in cloud operations including monitoring, cost management and infrastructure reliability
- Knowledge of Git and CI/CD tools like GitHub Actions
- Understanding of Agile/Scrum methodologies
- English proficiency at B2 level or higher
Nice to have
- Background in pharma or life sciences industry
- Experience with RESTful API and microservices development
- Knowledge of data governance, lineage or metadata management