Senior Data Engineer II
Elsevier · Mexico ·
- Seniority
- Senior
- Category
- Data engineering
Elsevier · Mexico ·
Do you want to join a collaborative, inclusive, and innovative team where your work helps improve healthcare outcomes worldwide?
About our Team:
The AIS (Academic Information Systems) DataOps team is responsible for managing the complex flow of data across teams, data centers, and organizational boundaries. Data is sanitized, consolidated, modeled, documented, and visualized to help tell a bigger story around how our products are used to help faculty members and researchers advance the missions of their organizations.
About the Role:
As a Senior Data Engineer II, you will contribute to building secure, scalable, and dependable data infrastructure that supports global teams and business needs. You will work collaboratively with colleagues across disciplines to ensure data moves efficiently and is accurate, well‑structured, and ready for analysis. Your work will support informed decision‑making and enable meaningful insights for both internal teams and customers.
Responsibilities:
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, maintain, and promote coding and technical standards.
Partner with DevOps to automate deployments and apply Infrastructure as Code (Iaff) for consistent environments.
Build reusable frameworks, modular components, and common deployment patterns using Airflow.
Document best practices and support knowledge sharing across teams.
Improve platform reliability and scalability through enhanced logging, monitoring, and observability.
Identify and address gaps in the data platform, support DataOps initiatives, and incorporate user feedback.
Requirements:
Demonstrated experience working with modern data technologies such as Airflow, Snowflake, and DBT, or comparable tools.
Experience with tools such as Tableau, Sisense, AWS, GitHub, Terraform, and Docker is beneficial but not required.
Ability to build and deploy data pipelines and ETL/ELT solutions using Python, SQL, Jinja, or similar languages.
Understanding of the Software Development Life Cycle (SDLC) and familiarity with DataOps and DevOps practices.
Experience working in Agile or iterative development environments with a focus on learning and improvement.
Effective communication skills and a collaborative mindset, with openness to feedback and diverse perspectives.
Familiarity with designing secure, scalable, and cost‑conscious cloud‑based data solutions.
Awareness of data governance, privacy, and security principles.
Willingness to go into the office twice a week in Reforma, Mexico City.
Work in a way that works for you:
We promote a healthy work/life balance across the organization. We provide a flexible and supportive environment where all colleagues can thrive. With numerous well‑being initiatives, shared parental leave, study assistance, and sabbaticals, we are committed to supporting your immediate responsibilities and long‑term aspirations.
Working for you:
We know that your well‑being and happiness are essential to a long and successful career. These are some of the benefits we are delighted to offer:
Private Medical/Dental Plan
Savings Fund
Life Insurance
Meal/Grocery Voucher
About the business:
We are a global leader in information and analytics. We help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine high‑quality information and vast datasets with analytics to support visionary science and research, health education and interactive learning, and exceptional healthcare and clinical practice.
What you do every day will help advance science and healthcare—contributing to human progress.
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
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