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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineering Architect - Evinova - **Company:** AstraZeneca - **Location:** Barcelona, Spain - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Apache HTTP Server, Bash Shell, Software as a Service, Computer Programming, Continuous Integration, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Amazon DynamoDB, Github, Identity and Access Management, Python (Programming Language), Key Management, Cloud Services, Prometheus, Data Streaming, TypeScript, AWS Cdk, Data Logging, Data Processing, Data Classification, Grafana, Apache Spark, Reliability of Systems, Infrastructure as Code (IaC), Amazon Virtual Private Cloud (VPC), Cloudformation, Amazon Relational Database Service, Containerization, Data Lakes, Pyspark, Kubernetes, AWS Glue, AWS Data Analytics, Apache Kafka, Data Management, Feature Extraction, Functional Programming, Cloudwatch, Terraform, Data Pipelines, Serverless Computing, Docker - **Published:** September 17, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=7fa9b069f0c6e8bf ## About the Role Ready to make an impact in your career? If you're passionate, growth-orientated and a true team player, we'll help you succeed. Here are some of the skills and capabilities we look for., Seize ownership and excel with autonomy to enjoy the constant rush of ground-breaking discovery. Your ability to anticipate sudden shifts and adapt swiftly will prove critical as you make your mark in an environment that rewards initiative and resilience., * AWS 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. * Open 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. * Streaming: Built production streaming pipelines with Kinesis Data Streams or MSK. Comfortable with exactly once semantics, 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 is expected, we currently use GitHub Actions, and some Terraform. * Data Modelling: Can design dimensional models, event schemas, and slowly changing dimensions. Understand the trade-offs between normalized and 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. PySpark or 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 of the tooling, patterns, and automation best practices. * Collaboration: 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. Required Experience & Qualifications * 10+ years in data engineering and data pattern type roles, with significant experience in SaaS and multi-tenant data platforms. Proven track record of mentoring team members in data platform related projects. * Cloud Expertise: Strong understanding of AWS services, including VPC, IAM, EC2, S3, RDS, Lambda, EKS, AWS WAF, and AWS CloudTrail. * Data Products: Expert knowledge of S3, RDS, DynamoDB, Kinesis, Glue, DataZone, Athena, RedShift Serverless,and AWS EventBridge. * Containerization & Orchestration: Deep proficiency in Docker, Kubernetes, Helm, and associated ecosystem tools. * CI/CD Proficiency: Expertise in CI/CD tools such as ArgoCD and GitHub Actions. * Infrastructure as Code (IaC): Advanced experience with AWS CDK (TypeScript preferred) and CloudFormation. * Security: Good knowledge of IAM, AWS KMS, encryption standards, AWS WAF, and security compliance frameworks including NIST. * Monitoring & Alerting: Good experience with OpenTelemetry, Prometheus, Grafana, AWS CloudWatch, and AWS CloudTrail for monitoring and incident response. * Data & ETL Pipelines: Extensive knowledge with 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 * Advanced expertise in AWS CDK, including building complex, reusable constructs and pipelines. * Experience with monitoring and logging tools such as Prometheus, Grafana, and AWS CloudWatch. * Exposure to multi-tenant SaaS platforms and best practices. * Experience working with AI tools and frameworks. Personal Attributes * Big Picture: Able to understand the strategic direction and help architect smaller initiatives with 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 about leveraging technology to solve complex problems and drive efficiency. * Customer-Focused: Dedicated to building infrastructure that delivers measurable business and customer value. ## Description Here, the answers aren't always available. So, you'll need to bring a fearless, self-starter mindset to navigate uncharted territories. You'll harness your ceaseless energy to discover and make the necessary connections with colleagues to shape the future and achieve maximum impact., Evinova, a healthtech leader, is seeking a passionate and experienced Data Engineering Architect to guide in the structure of the structure our platform-wide conformed data within our 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. In this pivotal role, you will design, implement, and optimize robust cloud-based data within the lakehouse, catalogue, pipelines, and operational frameworks that enable rapid innovation and deliver exceptional system reliability. You will be one of the senior-most data architects and engineers within the data foundation team; expected to be hands on, guide, and mentor the team. You will need to share your expertise in cloud data structures, optimizations, automation, and best practices with the whole of Evinova., Infrastructure Design & Management, Your wellbeing means a lot to us, and we're here to support you through all of life's ups and downs. That's why we offer an unpaid leave policy, annual leave, reduced-hours timetables and a host of benefits, including a retirement plan, long service award, and health and travel insurance. ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Monitoring as Code - Managing your dashboards at scale](https://www.wearedevelopers.com/videos/753-monitoring-as-code-managing-your-dashboards-at-scale) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [What Are The Top Skills Required For Azure Developers?](https://www.wearedevelopers.com/magazine/77-what-are-the-top-skills-required-for-azure-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)