Databricks Data Engineer – Cloud Pipelines & Hybrid Work

Capgemini; Wrocław; Hybrid; PLN 100,000 - 130,000; Full time

Benefits offered by this job

Yearly financial bonus

Private medical care

Life insurance

Access to training platforms

Home office package

Job summary

A global technology company is seeking an experienced Data Engineer to join their Insights & Data team. The role involves developing and maintaining data processing pipelines using Databricks, collaborating with senior engineers to implement scalable solutions, and ensuring data quality and security in cloud environments. Candidates should have hands-on data engineering experience, proficiency in Python, and familiarity with cloud platforms. A hybrid working model is offered alongside substantial training opportunities.

Qualifications

• Hands-on experience in data engineering and independent work on moderately complex tasks.
• Experience with Databricks in projects.
• Strong in Python for data transformation and automation.
• Usage of at least one cloud platform (AWS, Azure, GCP) in a production environment.
• Good communication skills in English.

Responsibilities

• Develop and maintain data processing pipelines using Databricks.
• Collaborate with senior engineers and architects on scalable data solutions.
• Work with cloud-native tools for large datasets.
• Ensure data quality, consistency, and security in cloud environments.
• Participate in code reviews and continuous improvement initiatives.

Skills

Data engineering

Python

Databricks

Cloud platforms (AWS, Azure, GCP)

SQL

Education

Relevant certifications (e.g., Databricks Certified Data Engineer Associate)

Tools

Terraform

CI/CD tools

Kafka

Spark Streaming

Job description

A global technology company is seeking an experienced Data Engineer to join their Insights & Data team. The role involves developing and maintaining data processing pipelines using Databricks, collaborating with senior engineers to implement scalable solutions, and ensuring data quality and security in cloud environments. Candidates should have hands-on data engineering experience, proficiency in Python, and familiarity with cloud platforms. A hybrid working model is offered alongside substantial training opportunities.