Build fully automated reusable data pipelines and operationalize them.
Maintain and build complex Data Orchestration
systems.
Collaborate with colleagues across IT and within Business Data teams to understand specific project requirements
and provide tailored, complete solutions that fit their needs, optimizing data architecture.
Ownership of the engineering
issues and resolving issues.
Support Data Ops and ML Ops activities.
Estimate requirements and define and promote best
practices.
Will also involve working closely with third party suppliers
Typical Accountabilities
- The Data Engineer will maintain deep working knowledge of data platforms/ data products and infrastructure aligned
with commercial IT
- Build, test, deploy and maintain data pipelines
- Perform a lead role in sprint planning, backlog refinement and prioritization along with sprint review activities.
- As needed and opportunistically, provides technical expertise to peers and 3rd party development suppliers to ensure
consistency in adherence to AZ IT and Commercial IT standards and processes
- Work with platform delivery resources to ensure validation of business and functional requirements as part of product
development responsibilities
business strategic roadmaps
data product.
- Serve as a mentor for junior staff members by conducting technical training sessions and reviewing project outputs
- Establish partnerships with 3rd party suppliers for staff augmentation and project capacity and provide technical
oversight for projects implemented through these suppliers
- Serve as an internal consultant for IT and business partners across regions and business areas (Commercial, Medical)
Continuous Improvement and Innovation
- Partners with Platform Success Lead(s) on continuous improvement opportunities within platform and product level
backlogs




- Identifies new hardware/software technologies to fit specialised business needs and configurations
- Identify issues with current processes and provide input on proposed changes to enhance effectiveness of IT
Education, Qualifications, Skills and Experience
Essential
- Bachelor's Degree or equivalent number of years of
experience in a Computer Science or Data Management
related field
- Demonstrated experience ( 3-5 years) in a data
engineering role with practical examples in developing
using modern data platforms to build, deploy, and
- The role holder will possess a blend of design skills
needed for Agile data development projects
- Proficiency or demonstratable passion for learning, in
data engineer techniques and testing methodologies
Strong data engineering skills with AWS cloud platform
- Experienced in Agile Development techniques and Methodologies
- 3-5 years of progressively responsible experience working with Databricks,
Workflows and Apache Airflow
- Experienced with building AWS or Azure cloud-based data pipeline
- 3-5 years of progressively responsible experience with Python, Spark
- Ability to interpret and communicate technical information into business
language
- Understanding of cloud architecture
- Strong communication and interpersonal skills
- Ability to work within both Agile and Waterfall development methodologies
- Proven experience of developing and managing relationships with 3rd party
suppliers
- Strong written and verbal communications skills
Desirable
- Experience with DevOps or DataOps concepts, preferable hands-on experience implementing continuous integration or highly automated end-to-end environments - Experience implementing a microservices architecture - Industry experience with data in large, complex data settings, consultancy or vendor experience - Experience in reusing of metadata and prebuilt components from cataloguing tools - Demonstrate initiative, strong customer orientation, and cross-cultural working

📌 Devops Data Engineer (Guadalajara)
🏢 Astrazeneca
📍 Guadalajara