Back to SearchSenior Data Engineer
Hybrid in Mexico
Data Software Engineering, Consultancy
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We are seeking a Senior Data Engineer to build, maintain, and evolve data platforms that power a specialized clinical study management application. You will own modern pipelines end-to-end to ensure high-quality, reliable, and available data for critical analytics and operations—apply to help shape trusted data at scale.
Responsibilities
- Design scalable and reliable data pipelines for ingestion, transformation, and consumption
- Build and operate ETL/ELT processes using modern data engineering approaches
- Develop and optimize data transformations using Python, PySpark, and dbt
- Design and administer Snowflake storage and processing solutions
- Define and apply best practices for data modeling, data architecture, and information governance
- Ensure data quality, consistency, and traceability across the data lifecycle
- Implement CI/CD strategies to automate testing and deployments for data pipelines
- Monitor platforms and resolve incidents affecting integrations and data processes
- Collaborate with development, product, analytics, and business teams to translate requirements into technical solutions
- Identify and implement improvements in performance, scalability, security, and maintainability
- Document architectures, technical processes, and engineering standards
Requirements
- 3+ years of data engineering experience
- Strong Python development experience
- Advanced PySpark experience for distributed data processing
- Hands-on Snowflake experience (modeling, optimization, administration)
- Practical dbt (Data Build Tool) experience for transformations
- CI/CD experience for data solutions
- Version control experience with Git
- Technical leadership ability to work autonomously and lead complex initiatives
- Strong analytical and problem-solving skills
- Effective communication skills with technical and functional teams
- Advanced English proficiency (C1, Advanced)
Nice to have
- Cloud platform experience (AWS, Azure, or GCP)
- Orchestration tool experience (Airflow or similar)
- Experience in regulated environments (healthcare, pharma, or clinical research)
- Data quality and pipeline observability knowledge
- Agile/Scrum experience