Experteer Overview

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In this role you will lead the design, implementation, and optimization of a cloud-based data lakehouse to empower products, data science, and agents. You will be one of the senior engineers, providing hands-on work and mentoring to the team while aligning data infrastructure with security and product goals. You’ll drive governance, scalability, and reliability across the data foundation, leveraging cutting-edge AWS technologies and modern data tooling.

The mission focuses on transforming life sciences data to enable faster, more impactful outcomes.

Compensaciones / Incentivos

- Design and manage AWS data services including Lake Formation, Glue, Athena, and EMR/Redshift Serverless to build an integrated data foundation
- Work with Open Table Formats (S3 Tables, Apache Iceberg preferred, or Delta Lake) focusing on partition, schema evolution, time travel and compaction
- Build and operate streaming pipelines with Kinesis Data Streams or MSK, ensuring exactly-once semantics and handling late-arriving data
- Define infrastructure as code (AWS CDK TS or CloudFormation); enable CI/CD for data pipelines with GitHub Actions and Terraform
- Model data with dimensional schemas and slowly changing dimensions; balance normalization vs denormalization for access patterns
- Implement governance and security including column-level and row-level controls and policy-driven data classification




- Develop ETL logic and data quality checks using Python or Spark; utilize PySpark or Spark Scala for distributed transforms
- Foster AI/ML exposure and practical tooling adoption; provide mentorship and technical leadership across tooling and automation
- Collaborate with product management and security to align data strategies with business goals and cohesive workflows
- Mentor junior and mid-level engineers and promote a learning-oriented, collaborative culture

Responsabilidades

- 10+ years in Data Engineering, with SaaS and multi-tenant data platforms experience
- Strong AWS expertise (VPC, IAM, EC2, S3, RDS, Lambda, EKS, WAF, CloudTrail)
- Expert knowledge of S3, RDS, DynamoDB, Kinesis, Glue, DataZone, Athena, Redshift Serverless, and EventBridge
- Proficiency with Docker, Kubernetes, Helm; xugodme CI/CD with ArgoCD and GitHub Actions; IaC with AWS CDK TS and CloudFormation
- Security literacy including IAM, KMS, encryption standards, NIST frameworks
- Experience with OpenTelemetry, Prometheus, Grafana, CloudWatch, and CloudTrail monitoring
- Extensive knowledge of AWS Glue, Kinesis, and Managed Kafka for real-time and batch data processing
- Strong programming and automation skills in TypeScript and Bash; PySpark or Spark Scala for data processing
- Multi-account AWS management experience using AWS Control Tower
- Excellent communication skills for stakeholder alignment and cross-functional collaboration

Requisitos principales

- in-person collaboration three days per week in Barcelona
- flexible working arrangement

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