AI Data Engineer (Data Engineering, Cloud Platform, Python)

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

Your role

As an AI Data Engineer, you will develop and maintain scalable data pipelines and AI-ready cloud infrastructure to support analytics, machine learning, and business intelligence solutions. You will work closely with engineering and AI teams to ensure reliable, secure, and high-quality data processing across multiple systems and platforms.

Your project

You will contribute to enterprise data transformation initiatives focused on modernizing data architecture, building cloud-native platforms, and supporting AI/ML applications. The project includes integration of multiple data sources, automation of workflows, and optimization of data processing systems.

Your client

Our client is an innovative organization focused on leveraging data and AI technologies to improve business operations and customer experiences.

Your tasks

• 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
• Monitor and improve data quality, reliability, and pipeline performance
• Collaborate with Data Scientists, Analysts, and Engineering teams
• Support deployment and automation of cloud-based data solutions
• Troubleshoot and resolve production data issues

Your profile

• 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
• Familiarity with Databricks, Snowflake, BigQuery, or Redshift
• Knowledge of AWS, Azure, or Google Cloud Platform
• Experience with Airflow, dbt, Docker, and Kubernetes
• Understanding of CI/CD pipelines and version control tools
• Familiarity with Vector Databases and LLM Frameworks is a plus
• Strong analytical and communication skills
• Ability to work in a fast-paced and collaborative environment

What You'll Love About Working Here

• Well-being culture with medical care, insurance, and wellness resources
• Access to over 70 training tracks with certification opportunities and educational platforms
• Continuous feedback and ongoing performance discussions
• Hybrid working model with support for home office setup

Equal Opportunity & Diversity

Capgemini is committed to diversity and inclusion, ensuring fairness in all employment practices. We evaluate individuals based on qualifications and performance, not personal characteristics, striving to create a workplace where everyone can succeed and feel valued.