SUMMARY OF THE JOB
We are seeking a seasoned Senior Data Engineer to design, build, and optimize our next-generation data platform. You will be responsible for architecting scalable data pipelines, managing large-scale distributed systems, and ensuring our data infrastructure in AWS and Databricks is robust and efficient. The idóneo candidate is a Spark expert with a deep understanding of the AWS ecosystem and a passion for automation.
MAIN ACTIVITIES / RESPONSIBILITIES
Pipeline Architecture: Design and implement complex batch and streaming ETL/ELT pipelines using Python, SQL, and Spark to process massive datasets.
Cloud Infrastructure: Leverage AWS Data Analytics services to build scalable, secure, and cost-effective data solutions.
Orchestration & DevOps: Manage and automate data workflows using Airflow , while utilizing Docker and ECS for containerized application deployment.
System Optimization: Monitor and tune the performance of distributed systems (Spark Cluster) to ensure high availability and low latency.
Infrastructure as Code:
Utilize AWS CloudFormation or Terraform to manage data infrastructure, ensuring repeatable and version-controlled environments.
Cost Optimization: Monitor and optimize AWS spend by selecting appropriate instance types (Spot vs. On-Demand) and refining data storage strategies.
Security & Compliance: Implement IAM roles, bucket policies, and encryption (KMS) to ensure data is secure at rest and in transit.
Collaboration: Work within an Agile framework to deliver iterative value, collaborating closely with Data Scientists and Stakeholders to translate business needs into technical reality.
JOB DIMENSIONS
List of direct reports:
Up to 2 Direct Reports, and around 15 externals
Key interfaces, stakeholders and relationships:
Internal:
GDS: product manager, application manager, data & analytics & AI team
Country business stakeholders
External : 3rd party vendors
PROFILE REQUIRED
Experience: Minimum 4+ years of hands-on experience in acti
📌 Senior Data Engineer (Madrid)
🏢 Holcim
📍 Madrid