Data Operations Engineer

Overview

AstraZeneca is an innovation-driven global biopharmaceutical company focused on the discovery, development and commercialization of prescription medicines, primarily for the treatment of cardiovascular, renal and metabolic, respiratory and immunological, oncological and rare diseases.

Our Barcelona hub has been created to achieve the next wave of breakthroughs that help us do what’s never been done before, as we expand our global footprint. Harnessing data and using the best technology solutions available allow us to positively impact science.

Join our innovative Data & AI Accelerators platform as a Data Ops Engineer within the R&D data lake team. Our mission is to accelerate scientific innovation in the pharmaceutical industry by enabling seamless, secure, and compliant management of R&D data. We are seeking a dedicated and skilled professional to drive operational efficiency and streamline service-level agreements (SLAs) for our data lake.

Key Responsibilities

Drive Operational Efficiency:

• Optimise processes to enhance the performance and reliability of the data lake.

• Analyse bottlenecks and devise solutions to improve data flow and delivery times.

• Manage and reduce SLAs:

• Collaborate with cross-functional teams to expedite issue resolution.

• Implement strategies to ensure consistent, high-performing service delivery.

Cloud Infrastructure Management:

• Manage cloud-based infrastructure for data ingestion, storage, and security.

• Identify and resolve issues impacting cloud infrastructure performance.

Data Ingestion and Storage:

• Oversee the ingestion of complex research data sets into the data lake.

• Ensure data is securely and efficiently stored and managed.

Data Curation and Quality Assessment:

• Develop and implement data curation processes to maintain data quality.

• Conduct regular assessments to ensure data accuracy, integrity, and compliance.

Secure Data Access:

• Ensure secure access protocols are in place and adhered to for sensitive research data.

• Collaborate with security teams to address any vulnerabilities in data access.
  

Technical Skills

Candidates are not required to know all these tools to apply, but familiarity with more tools is beneficial as this role will involve using many of them at different times.

AWS:

• Data services: S3, Glue

• Other services: SNS, SQS, Lambda, ECS, ECR

Infrastructure as Code (IaC):

• CloudFormation

• Terraform is a plus

Programming Languages:

• Python

• Java is a plus

Automation and CI/CD:

• Jenkins

• GitHub Actions is a plus

Databases:

• RDBMS of choice (Postgres)

• Snowflake is a plus

ETL Tools:

• Talend

• Airflow and FiveTranare a plus

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.

• Proven experience (2-5 years) in data operations, cloud infrastructure, and data management.

• Familiarity with MLOps and AI engineering practices is a plus.

• Strong problem-solving skills and ability to work in a fast-paced environment.

• Excellent communication and collaboration skills to work with cross-functional teams.

Domain Knowledge

• Experience in biomedical research or healthcare data (internships or projects) is a plus.

• Understanding of data privacy and regulatory compliance in the life sciences is a plus.