Snowflake Data Engineer — Build Scalable Cloud Pipelines

Capgemini; Kraków; Hybrid; PLN 180,000 - 240,000; Full time

Benefits offered by this job

Medicover health

Multisport card

Hybrid work model

Training tracks access

Job summary

Capgemini Kraków is seeking a capable Data Engineer to design, develop, and maintain Snowflake data pipelines for multiple business functions. You will collaborate with cross-functional teams to implement scalable data solutions, optimize data models, and ensure data integrity and security across the lifecycle.

The role involves migrating from on-premise warehouses to Snowflake and developing AI/ML solutions, with a strong emphasis on GenAI and NLP technologies.

Qualifications

• At least 3 years of experience in Big Data or Cloud projects handling large or unstructured datasets, with hands-on Snowflake experience.
• Understanding of Snowflake pricing and cost optimization strategies.
• Experience designing data transformation pipelines in Snowflake or via service partners.
• Familiarity with Snowflake security model and cloud platform capabilities.
• Basic SQL and one programming language (Python/Scala/Java/bash).
• Very good command of English.

Responsibilities

• Design, develop, and maintain Snowflake data pipelines to support business functions.
• Collaborate with cross-functional teams to understand data requirements and implement scalable solutions.
• Optimize data models and schemas for performance and efficiency.
• Ensure data integrity, quality, and security across the data lifecycle.
• Implement monitoring and alerting systems; plan migrations from on-prem to Snowflake.
• Develop AI/ML and Generative AI solutions; stay updated on best practices.

Skills

Snowflake experience

Big Data

SQL

Python/Scala/Java

Cloud platforms

Tools

Snowflake

Job description

Capgemini Kraków is seeking a capable Data Engineer to design, develop, and maintain Snowflake data pipelines for multiple business functions. You will collaborate with cross-functional teams to implement scalable data solutions, optimize data models, and ensure data integrity and security across the lifecycle.

The role involves migrating from on-premise warehouses to Snowflake and developing AI/ML solutions, with a strong emphasis on GenAI and NLP technologies.