Azure Data Engineer: Build Scalable Cloud Data Pipelines

Capgemini; Kraków; Hybrid; PLN 180,000 - 260,000; Full time

Benefits offered by this job

Medicover medical care

Multisport card

Capgemini Helpline

Job summary

Capgemini is seeking a data engineer to design and implement Azure-based data solutions for large-scale datasets in a hybrid work environment. The role focuses on building scalable data pipelines with Azure Data Factory, Databricks, or Snowflake, and collaborating with architects to enforce best practices in data engineering.

Ideal candidates have strong Azure experience, Python expertise for data processing and automation, and excellent English communication skills.

Qualifications

• Strong experience in data engineering, including working with Azure.
• Strong Python for data processing and automation.
• Hands-on experience with Databricks, Snowflake, or Microsoft Fabric.
• Strong communication skills and very good English language skills.

Responsibilities

• Design and implement Azure-based data solutions for large-scale and unstructured datasets.
• Develop and optimize data pipelines using Azure Data Factory, Databricks, or Snowflake.
• Collaborate with solution architects to define and implement best practices in data engineering.
• Ensure data quality, scalability, and security across all Azure-based solutions.

Skills

Python for data processing

Strong communication

Excellent English

Tools

Databricks

Snowflake

Microsoft Fabric

Docker

Kubernetes

Job description

Capgemini is seeking a data engineer to design and implement Azure-based data solutions for large-scale datasets in a hybrid work environment. The role focuses on building scalable data pipelines with Azure Data Factory, Databricks, or Snowflake, and collaborating with architects to enforce best practices in data engineering.

Ideal candidates have strong Azure experience, Python expertise for data processing and automation, and excellent English communication skills.