This is an in-office role based in Barcelona, ES, with a requirement to work a minimum of three days per week on‑site. Remote or travel flexibility is not available.

We are seeking a highly skilled and experienced Senior Data Engineer to join our dynamic team. You will significantly impact the role of data engineering on the delivery of Data Products to the Oncology R&D organisation. Ensuring we are continuously advancing our data stack as well as our automation and observability capabilities will be central to your work.

Main Duties and Responsibilities

Building and maintaining the infrastructure and pipelines for extracting, transforming, and loading data for use in data products and analyses.
Working with data scientists and other stakeholders to understand the data needs and requirements of the organization and designing data systems and pipelines to meet these needs.
Implementing data ingestion, transformation, and storage systems in a FAIR and high-quality way
Ensuring the reliability, scalability, and performance of data systems and pipelines.
Implementing data governance policies and procedures to ensure the security, privacy, and integrity of data.
Collaborating with other members of the data team to build and maintain data products and services.
Staying up-to-date with new technologies and best practices in the field of data engineering

Essential Requirements

Computer Science, Engineering, or Bioinformatics background (Master level) with 5 years of relevant experience
Deep knowledge of Python and vast experience with Python data and scientific libraries like pandas, numpy/scipy, polars, etc
An ability to interact with various data sources, both structured and unstructured (e.g. HDFS, SQL, noSQL)
Experience working across multiple scientific compute environments to create data workflows and pipelines (e.g. HPC, cloud, Unix/Linux systems)
Understanding of the FAIR data principles and how they apply to the delivery of integrated X-Omics solutions
Deep understanding of typical data quality issues, cleaning and masking techniques

Desirable Skills

Experience working with metadata models, controlled vocabularies and ontologies
Experience with deploying data pipelines using orchestration services: Airflow/Prefect/AWS Glue/Dagster/etc.
Experience using AWS services: S3/EBS, EC2, CloudWatch, SNS and Lambda.
Understanding of software development, testing and quality processes, experience with testing frameworks and documentation
Expertise with biological/health data, especially NGS and other ‘omic technologies.
Ability to understand, map, integrate, and document complex data relationship and business rules.

#EAI

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.

Associate Director Data Engineering

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