Evinova isseekinga passionate and experiencedData Foundation Engineering Lead toguideinthe transformation of ourplatform-wide data foundationtoenable our products, data science, andagents to deliver category leading capabilities. Join us inleveragingcutting-edgetechnology, data, and AI to revolutionize life sciences and improve billions of lives globally.

In this pivotal role, you will design, implement, andoptimizerobust cloud-based datalakehouseinfrastructure and operational frameworks that enable rapid innovation and deliver exceptional system reliability.You will beone of the senior-mostengineerswithin the team;expected to be hands on, guide,and mentor the team.You will need to share yourexpertisein cloud data infrastructure, automation, and best practiceswith the whole ofEvinova.

Key Responsibilities

Infrastructure Design & Management:

- AWS Data Services: Deep hands-on experience with Lake Formation, Glue (ETL + Catalogue+ Schema Registry), Athena, and at least one ofEMR/ Redshift Serverless. You understand how these compose, not just how each works in isolation.

- Open Table Formats: Production experience withS3 Tables, Apache Iceberg (preferred),or Delta Lake. You understand partition evolution, schema evolution, time travel, and compaction — and when eachmatter.

- Streaming: Built production streaming pipelines with Kinesis Data Streams or MSK. Comfortable withexactly oncesemantics, windowing, late-arriving data, and backpressure.

- Infrastructure as Code: AWS CDK (TypeScript ) or CloudFormation. You define infrastructure in code, not in the console. CI/CD for data pipelines isexpected,we currently use GitHub Actions, and some Terraform.

- Data Modelling: Can design dimensional models, event schemas, and slowly changing dimensions. Understand the trade-offs betweennormalizedand denormalized storage for different access patterns.

- Governance and Security: Practical experience implementing column-level security, row-level filtering, or tag-based access control. Understands how data classification drives policy.

- Python or Spark: For ETL logic, feature extraction, and data quality validation.PySparkor Spark Scala for distributed transforms.

- AI & Machine Learning: Exposure to AI tools and frameworks is a plus.

- Mentorship & Leadership:



Mentor and guide junior and mid-level engineers, fostering a culture of learning and collaboration. Provide technical leadership in the adoption ofthe tooling, patterns, andautomationbest practices.

- Collaboration: Partner with cross-functional teams, including product management and security, to aligndata foundationstrategies with business goals and ensure cohesive development and operational workflows.

Required Experience & Qualifications:

- Experience: 10+ years inData Engineeringroles, withsignificant experiencein SaaS and multi-tenantdataplatforms. Proventrack recordof mentoring team membersindata platformrelated projects.

- Cloud Expertise: Strongunderstandingof AWS services, including VPC, IAM, EC2, S3, RDS, Lambda, EKS, AWS WAF, and AWS CloudTrail.

- Data Products: Expert knowledge ofS3, RDS,DynamoDB, Kinesis,Glue,DataZone, Athena, RedShift Serverless,and AWSEventBridge.

- Containerization & Orchestration: Deepproficiencyin Docker, Kubernetes, Helm, and associated ecosystem tools.

- CI/CD Proficiency: Expertisein CI/CD tools such asArgoCDand GitHub Actions.

- Infrastructure as Code (IaC): Advanced experience with AWS CDK (TypeScript preferred) and CloudFormation.

- Security: Goodknowledge of IAM, AWS KMS, encryption standards, AWS WAF, and security compliance frameworks including NIST.

- Monitoring & Alerting: GoodexperiencewithOpenTelemetry, Prometheus, Grafana, AWS CloudWatch, and AWS CloudTrail for monitoring and incident response.

- Data & ETL Pipelines: Extensive knowledgewith AWS Glue, AWS Kinesis,and Managed Kafka for real-time and batch data processing.

- Programming & Automation: Strong scripting and automation skills using TypeScript and Bash.

- Multi-Account AWS Management: Experience managing multiple AWS accounts with AWS Control Tower.

- Communication & Collaboration:



Exceptional verbal and written communication skills, with the ability to explain complex technical concepts to diverse stakeholders.

Desired Experience & Qualifications

- Advancedexpertisein AWS CDK, including building complex, reusableconstructsand pipelines.

- Experience with monitoring and logging tools such as Prometheus, Grafana, and AWS CloudWatch.

- Exposure tomulti-tenant SaaS platforms and best practices.

- Experience working with AI tools and frameworks.

Personal Attributes

- Big Picture: Able to understand the strategic directionand helparchitectsmaller initiativeswith the direction in mind.

- Mentor & Leader: Enjoys mentoring team members,and fostering a collaborative, innovation-driven team culture.

- Organized & Adaptable: Able to manage multiple priorities and thrive in a fast-paced environment.

- Innovative: Passionate aboutleveragingtechnology to solve complex problems and drive efficiency.

- Customer-Focused: Dedicated to building infrastructure that delivers measurable business and customer value.

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not adaptable. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

Date Posted

29-jul-2026

Closing Date

12-ago-2026

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.

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📌 Data Foundation Engineering Lead - Evinova (Barcelona)
🏢 Astrazeneca
📍 Barcelona