Senior Data Engineer - Evinova

AstraZeneca
Barcelona, Spain
7 days ago
Apply on www.buscojobs.com.es
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours

Tech stack

Amazon Web Services Amazon Elastic Compute Cloud Amazon S3 Software as a Service Cloud Database Continuous Integration Information Engineering Data Infrastructure Extract Transform Load (ETL) Amazon DynamoDB Github Identity and Access Management
+21 more
Python (Programming Language) Prometheus TypeScript AWS Cdk Scripting Grafana Apache Spark Amazon Virtual Private Cloud (VPC) Cloudformation Amazon Relational Database Service Data Lakes Pyspark Kubernetes AWS Data Analytics Apache Kafka Data Management Functional Programming Cloudwatch Data Pipelines Serverless Computing Docker

Job description

OverviewIn this on-site Barcelona role, you will build and automate a robust data foundation to empower product teams, data science, and agents.You’ll design and implement cloud-based data pipelines and lakehouse components, driving reliable, scalable data platforms.You’ll mentor peers and share best practices across the organization, shaping how data supports healthcare innovation.Expect hands-on work with cutting-edge AWS data services and modern data tooling to enable rapid, impactful decision-making.ResponsabilidadesDesign and manage cloud data infrastructure across AWS services (Lake Formation, Glue, Athena, EMR/Redshift Serverless)Develop and optimize table formats (Iceberg preferred; Delta Lake) and handle partition/schema evolutionBuild and operate streaming pipelines (Kinesis/MSK) with exactly-once semantics and windowingImplement infrastructure as code (CDK/CloudFormation) and CI/CD for data pipelines (GitHub Actions, TerraformModel data for analytics with dimensional models and slowly changing dimensionsEnforce governance and security (column-level/row-level security, tag-based access)Develop ETL logic with Python or Spark; leverage PySpark/Scala for distributed transformsMentor junior engineers and promote tooling adoption and best practicesCollaborate with product management and security to align data foundation with business goalsRequisitos principales7+ years of hands-on data engineering experience in SaaS/multi-tenant environmentsStrong AWS expertise across VPC, IAM, EC2, S3, RDS, Lambda, EKS, WAF, CloudTrailExtensive experience with S3, RDS, DynamoDB, Kinesis, Glue, DataZone, Athena, Redshift Serverless, EventBridgeProficiency in Docker, Kubernetes, Helm; CI/CD with ArgoCD, GitHub ActionsIaC with AWS CDK (TypeScript) and CloudFormationSecurity knowledge including IAM, KMS, encryption, AWS WAF, NIST frameworksMonitoring/observability with OpenTelemetry, Prometheus, Grafana, CloudWatch/CloudTrailETL/real-time data pipelines with Glue, Kinesis, Managed Kafka; scripting in TypeScript and BashMulti-account AWS management (AWS Control Tower)Strong communication skills for cross-functional collaborationMentorshipCollaborationOrganizedAWS Lake FormationAWS Glue (ETL, Catalog, Schema Registry)Athena

Requirements

Expect hands-on work with cutting-edge AWS data services and modern data tooling to enable rapid, impactful decision-making. ResponsabilidadesDesign and manage cloud data infrastructure across AWS services (Lake Formation, Glue, Athena, EMR/Redshift Serverless)Develop and optimize table formats (Iceberg preferred; Delta Lake) and handle partition/schema evolutionBuild and operate streaming pipelines (Kinesis/MSK) with exactly-once semantics and windowingImplement infrastructure as code (CDK/CloudFormation) and CI/CD for data pipelines (GitHub Actions, TerraformModel data for analytics with dimensional models and slowly changing dimensionsEnforce governance and security (column-level/row-level security, tag-based access)Develop ETL logic with Python or Spark; leverage PySpark/Scala for distributed transformsMentor junior engineers and promote tooling adoption and best practicesCollaborate with product management and security to align data foundation with business goals Requisitos principales7+ years of hands-on data engineering experience in SaaS/multi-tenant environmentsStrong AWS expertise across VPC, IAM, EC2, S3, RDS, Lambda, EKS, WAF, CloudTrailExtensive experience with S3, RDS, DynamoDB, Kinesis, Glue, DataZone, Athena, Redshift Serverless, EventBridgeProficiency in Docker, Kubernetes, Helm; CI/CD with ArgoCD, GitHub ActionsIaC with AWS CDK (TypeScript) and CloudFormationSecurity knowledge including IAM, KMS, encryption, AWS WAF, NIST frameworksMonitoring/observability with OpenTelemetry, Prometheus, Grafana, CloudWatch/CloudTrailETL/real-time data pipelines with Glue, Kinesis, Managed Kafka; scripting in TypeScript and BashMulti-account AWS management (AWS Control Tower)Strong communication skills for cross-functional collaborationMentorshipCollaborationOrganizedAWS Lake FormationAWS Glue (ETL, Catalog, Schema Registry)Athena

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.buscojobs.com.es
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

2:07 min

Inspecting default bridge architectures and custom Docker networks

Oliver Seitz Oliver Seitz · World Congress 2025

6:36 min

Funding open source through GitHub Accelerator and Sponsors

Stormy Peters · World Congress 2023

4:32 min

Harnessing Spark with Python using PySpark and Py4J

Ayon Roy · LIVE

3:37 min

Scaling machine learning pipelines from prototypes to petabytes

Julian Joseph · LIVE

2:57 min

Core technical practices for robust data engineering

Sandhya Menon Sandhya Menon · World Congress 2026 Europe

Videos

See all

Related articles

See all