Senior Data Engineer - Spark & AWS Platform Architect

Holcim; Madrid; On-site; EUR 90,000 - 130,000; Full time

Job summary

Holcim seeks a seasoned Senior Data Engineer to design, build and optimize a next-generation data platform. You will architect scalable pipelines, manage large distributed systems in AWS and Databricks, and ensure robust data infrastructure with automation and cost efficiency.

The role emphasizes Spark expertise, data lake/warehouse design (S3, Redshift, Athena), and orchestration via Airflow. Collaboration with data scientists and stakeholders in an Agile setup is essential, with emphasis on

Qualifications

• 4+ years hands-on experience in Big Data environments and 2+ years in AWS data analytics.
• Proficient in Spark clusters (EMR) and data lake design on S3/Parquet/Delta.
• Experience with serverless ETL (Glue) and data cataloging, and with Airflow-based orchestration.
• Strong knowledge of CI/CD for data pipelines, version control, and documentation.
• Experience with data mesh concepts and lakehouse architectures using Delta Lake.

Responsibilities

• Design and implement batch and streaming ETL/ELT pipelines using Python, SQL, and Spark.
• Leverage AWS Data Analytics services to build scalable, secure data solutions.
• Manage and automate data workflows using Airflow and containerization with Docker/ECS.
• Monitor and optimize Spark clusters for high availability and low latency.
• Use IaC (CloudFormation or Terraform) to maintain repeatable environments.
• Optimize AWS spend and data storage strategies.
• Collaborate with data scientists and stakeholders in an Agile environment.

Skills

Spark

Python

SQL

Big Data

English communication

Education

Bachelor's degree in Computer Science/Engineering/Mathematics

Tools

Airflow

Docker

ECS

AWS

Databricks

Terraform

CloudFormation

Kinesis / MSK

Job description

Holcim seeks a seasoned Senior Data Engineer to design, build and optimize a next-generation data platform. You will architect scalable pipelines, manage large distributed systems in AWS and Databricks, and ensure robust data infrastructure with automation and cost efficiency.

The role emphasizes Spark expertise, data lake/warehouse design (S3, Redshift, Athena), and orchestration via Airflow. Collaboration with data scientists and stakeholders in an Agile setup is essential, with emphasis on