ppEvinova is seeking a passionate and experienced bData Foundation Engineering Lead /b to guide in the transformation of our platform-wide data foundation to enable our products, data science, and agents to deliver category leading capabilities. Join us in leveraging cutting-edge technology, data, and AI to revolutionize life sciences and improve billions of lives globally. /p pIn this pivotal role, you will design, implement, and optimize robust cloud-based data lakehouse infrastructure and operational frameworks that enable rapid innovation and deliver exceptional system reliability. You will be one of the senior-most engineers within the team; expected to be hands on, guide, and mentor the team. You will need to share your expertise in cloud data infrastructure, automation, and best practices with the whole of Evinova. /p h3Key Responsibilities /h3 pInfrastructure Design Management: /p ul liAWS Data Services: Deep hands‑on experience with Lake Formation, Glue (ETL + Catalogue + Schema Registry), Athena, and at least one of EMR / Redshift Serverless. You understand how these compose, not just how each works in isolation. /li liOpen Table Formats: Production experience with S3 Tables, Apache Iceberg (preferred), or Delta Lake. You understand partition evolution, schema evolution, time travel, and compaction — and when each matter. /li liStreaming: Built production streaming pipelines with Kinesis Data Streams or MSK. Comfortable with exactly once semantics, windowing, late‑arriving data, and backpressure. /li liInfrastructure as Code: AWS CDK (TypeScript) or CloudFormation. You define infrastructure in code, not in the console. CI/CD for data pipelines is expected, we currently use GitHub Actions, and some Terraform. /li liData Modelling: Can design dimensional models, event schemas, and slowly changing dimensions. Understand the trade‑offs between normalized and denormalized storage for different access patterns. /li liGovernance and Security: Practical experience implementing column‑level security, row‑level filtering, or tag‑based access control. Understands how data classification drives policy. /li liPython or Spark: For ETL logic, feature extraction, and data quality validation. PySpark or Spark Scala for distributed transforms. /li liAI Machine Learning: Exposure to AI tools and frameworks is a plus.



/li liMentorship Leadership: Mentor and guide junior and mid‑level engineers, fostering a culture of learning and collaboration. Provide technical leadership in the adoption of the tooling, patterns, and automation best practices. /li liCollaboration: Partner with cross‑functional teams, including product management and security, to align data foundation strategies with business goals and ensure cohesive development and operational workflows. /li /ul h3Required Experience Qualifications /h3 ul liExperience: 10+ years in Data Engineering roles, with significant experience in SaaS and multi‑tenant data platforms. Proven track record of mentoring team members in data platform related projects. /li liCloud Expertise: Strong understanding of AWS services, including VPC, IAM, EC2, S3, RDS, Lambda, EKS, AWS WAF, and AWS CloudTrail. /li liData Products: Expert knowledge of S3, RDS, DynamoDB, Kinesis, Glue, DataZone, Athena, RedShift Serverless, and AWS EventBridge. /li liContainerization Orchestration: Deep proficiency in Docker, Kubernetes, Helm, and associated ecosystem tools. /li liCI/CD Proficiency: Expertise in CI/CD tools such as ArgoCD and GitHub Actions. /li liInfrastructure as Code (IaC): Advanced experience with AWS CDK (TypeScript preferred) and CloudFormation. /li liSecurity: Good knowledge of IAM, AWS KMS, encryption standards, AWS WAF, and security compliance frameworks including NIST. /li liMonitoring Alerting: Good experience with OpenTelemetry, Prometheus, Grafana, AWS CloudWatch, and AWS CloudTrail for monitoring and incident response. /li liData ETL Pipelines: Extensive knowledge with AWS Glue, AWS Kinesis, and Managed Kafka for real‑time and batch data processing. /li liProgramming Automation: Strong scripting and automation skills using TypeScript and Bash. /li liMulti‑Account AWS Management: Experience managing multiple AWS accounts with AWS Control Tower. /li liCommunication Collaboration:



Exceptional verbal and written communication skills, with the ability to explain complex technical concepts to diverse stakeholders. /li /ul h3Desired Experience Qualifications /h3 ul liAdvanced expertise in AWS CDK, including building complex, reusable constructs and pipelines. /li liExperience with monitoring and logging tools such as Prometheus, Grafana, and AWS CloudWatch. /li liExposure to multi‑tenant SaaS platforms and best practices. /li liExperience working with AI tools and frameworks. /li /ul h3Personal Attributes /h3 ul liBig Picture: Able to understand the strategic direction and help architect smaller initiatives with the direction in mind. /li liMentor Leader: Enjoys mentoring team members, and fostering a collaborative, innovation‑driven team culture. /li liOrganized Adaptable: Able to manage multiple priorities and thrive in a fast‑paced environment. /li liInnovative: Passionate about leveraging technology to solve complex problems and drive efficiency. /li liCustomer‑Focused: Dedicated to building infrastructure that delivers measurable business and customer value. /li /ul pWhen 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 versátil. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world. /p pAstraZeneca 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. /p /p #J-18808-Ljbffr

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