Senior Databricks Data Engineer — Cloud Analytics & AI

Capgemini; Województwo pomorskie; On-site; PLN 180,000 - 280,000; Full time

Job summary

Capgemini Poland is seeking a data engineer to design and implement data processing solutions using Databricks and Python in a cloud-first environment. You will build robust data pipelines for large-scale datasets across AWS, Azure, or GCP, applying best practices in data engineering.

Work closely with solution architects to ensure data quality, security and scalability, and communicate effectively in English within a collaborative Capgemini team.

Qualifications

• Strong experience in data engineering with at least 1 year of hands-on Databricks expertise.
• Strong experience in Python for automation and data transformation.
• Experience with at least one major cloud platform (AWS, Azure, or GCP).
• Strong communication skills and strong English language skills.
• SQL knowledge and data modeling (nice to have).
• DevOps, CI/CD, and Infrastructure as Code (Terraform, Bicep) (nice to have).
• Real-time data streaming technologies such as Kafka or Spark Streaming (nice to have).
• Cloud storage solutions like Data Lake, Snowflake, or Synapse (nice to have).
• Hands-on experience with PySpark for distributed data processing (nice to have).
• Relevant certifications such as Databricks Certified Data Engineer Associate (nice to have).

Responsibilities

• Design and implement data processing solutions using Databricks for large-scale and diverse datasets.
• Design, build, and enhance data pipelines with Python and cloud-native tools.
• Work closely with solution architects to define and uphold best practices in data engineering.
• Ensure data consistency, security, and scalability within cloud-based environments.

Skills

Databricks

Python

Cloud platforms

Data engineering

English proficiency

Tools

Terraform

PySpark

Kafka

Snowflake

Synapse

Job description

Capgemini Poland is seeking a data engineer to design and implement data processing solutions using Databricks and Python in a cloud-first environment. You will build robust data pipelines for large-scale datasets across AWS, Azure, or GCP, applying best practices in data engineering.

Work closely with solution architects to ensure data quality, security and scalability, and communicate effectively in English within a collaborative Capgemini team.