TL;DR
Senior Data Engineer (Data Science/ML): Building secure, scalable, and reliable data infrastructure and pipelines to support global operations with an accent on data orchestration, transformation, and platform reliability. Focus on designing deployable ETL/ELT solutions, automating deployments, and ensuring high-quality data delivery for analysis and decision-making.
Location: Remote, Mexico
Company
Global leader in information and analytics helping researchers and healthcare professionals advance science and improve health outcomes worldwide.
What you will do
- Design and implement robust data orchestration and transformation solutions.
- Ensure reliable delivery of high-quality data for analysis, reporting, and sharing.
- Collaborate with cross-functional teams to define and promote coding and technical standards.
- Partner with DevOps to automate deployments and apply Infrastructure as Code for consistent environments.
- Build reusable frameworks and modular components using Airflow.
- Improve platform reliability and scalability through enhanced logging, monitoring, and observability.
Requirements
- Experience with modern data stack technologies such as Airflow, Snowflake, DBT; familiarity with Tableau, Sisense, AWS, GitHub, Terraform, Docker.
- Ability to create deployable data pipelines and ETL/ELT solutions using Python, SQL, or Jinja.
- Knowledge of SDLC, DataOps, and DevOps practices.
- Active participation in Agile environments and commitment to continuous improvement.
- Strong communication and collaboration skills.
- Familiarity with designing secure, scalable, and cost-effective cloud-based data solutions and understanding of data governance, privacy, and security practices.
Culture & Benefits
- Flexible and supportive work environment promoting work/life balance.
- Private Medical/Dental Plan, Savings Fund, Life Insurance, Meal/Grocery Voucher.
- Well-being initiatives, shared parental leave, study assistance, and sabbaticals.