Hybrid AI Data Engineer — Cloud Pipelines & AI-Ready Data

Capgemini; Warszawa; Hybrid; PLN 120,000 - 160,000; Full time

Benefits offered by this job

Medical care

Insurance

Wellness resources

Access to training tracks

Job summary

Capgemini is looking for an experienced AI Data Engineer in Warsaw, Poland, to develop and maintain scalable data pipelines and AI-ready infrastructure. The candidate will work with engineering teams on data processing and analytics solutions.

Responsibilities include building ETL/ELT pipelines, processing large datasets, and integrating data from various sources. A minimum of 3 years of experience in data engineering and strong skills in Python and SQL are required. The position supports a hybrid working model and offers various well-being resources.

Qualifications

• 3+ years of experience in Data Engineering or related roles.
• Strong programming skills in Python and SQL.
• Experience with PySpark, Apache Spark, Kafka, or Hadoop.

Responsibilities

• Develop and maintain ETL/ELT pipelines for enterprise data platforms.
• Process and transform large-scale structured and unstructured datasets.
• Support AI and machine learning data preparation workflows.
• Integrate data from APIs, databases, and cloud services.

Skills

Data Engineering

Python

SQL

ETL/ELT pipelines

PySpark

Apache Spark

Docker

Kubernetes

Tools

AWS

Azure

Google Cloud Platform

Airflow

Databricks

Snowflake

BigQuery

Redshift

Job description

Capgemini is looking for an experienced AI Data Engineer in Warsaw, Poland, to develop and maintain scalable data pipelines and AI-ready infrastructure. The candidate will work with engineering teams on data processing and analytics solutions.

Responsibilities include building ETL/ELT pipelines, processing large datasets, and integrating data from various sources. A minimum of 3 years of experience in data engineering and strong skills in Python and SQL are required. The position supports a hybrid working model and offers various well-being resources.