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 adecuado candidate is a Spark expert with a deep understanding of the AWS ecosystem and a passion for automation.

MAIN ACTIVITIES / RESPONSIBILITIES

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Pipeline Architecture: Design and implement complex batch and streaming ETL/ELT pipelines using Python, SQL, and Spark to process massive datasets.

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Cloud Infrastructure: Leverage AWS Data Analytics services to build scalable, secure, and cost-effective data solutions.

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Orchestration & DevOps: Manage and automate data workflows using Airflow, while utilizing Docker and ECS for containerized application deployment.

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System Optimization: Monitor and tune the performance of distributed systems (Spark Cluster) to ensure high availability and low latency.

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Infrastructure as Code:



Utilize AWS CloudFormation or Terraform to manage data infrastructure, ensuring repeatable and version-controlled environments.

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Cost Optimization: Monitor and optimize AWS spend by selecting appropriate instance types (Spot vs. On-Demand) and refining data storage strategies.

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Security & Compliance: Implement IAM roles, bucket policies, and encryption (KMS) to ensure data is secure at rest and in transit.

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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:

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Up to 2 Direct Reports, and around 15 externals

Key interfaces, stakeholders and relationships:

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Internal:

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GDS: product manager, application manager, data & analytics & AI team

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Country business stakeholders

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External : 3rd party vendors

PROFILE REQUIRED

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Experience: Min

📌 Senior Data Engineer (Madrid)
🏢 Holcim Group
📍 Madrid