PLES DXC TECHNOLOGY POLSKA sp. z o.o.
Snowflake Data Engineer with German
Data engineer at DXC Technology building enterprise-scale data platforms on Snowflake for a German client: designing ETL/ELT pipelines, dbt transformations, and data models for reporting and analytics. Core stack is Snowflake, SQL, Python, dbt, Git/CI-CD, and a major cloud platform, with communication in German (B2+).
- Compensation
- Not disclosed
- Location
- Wrocław, Poland
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Data engineering
- Posted
Skills
Must have
- 3–5 years of experience as a Data Engineer, including in-depth practical experience with Snowflake as a data warehouse
- Strong hands-on Snowflake development: databases, schemas, stages, streams/tasks, views, stored procedures, performance tuning, access management
- Good understanding of data warehouse design, dimensional modeling, Kimball methodology, data marts, star/snowflake schemas
- Excellent SQL skills for efficient transformations, analytical queries, and reusable data models
- Experience building production-grade ETL/ELT pipelines with modern orchestration tools
- In-depth experience with dbt (development, testing, deployment of models)
- Good Python skills for data processing, automation, testing, and integration
- Practical understanding of Data Lake and Lakehouse concepts (ingestion, storage, governance, analytics enablement)
- Practical experience with at least one cloud platform (preferably Azure, AWS, or GCP): storage, compute, networking, identity, security basics
- Practical knowledge of Git, Azure DevOps or similar, code reviews, testing, and CI/CD practices
- Good communication skills with technical and business stakeholders
- Good command of German (minimum B2)
Nice to have
- Hands-on experience with Snowpark, Snowpipe, dynamic tables, data sharing, masking policies, or Snowflake Native Apps
- Experience with Airflow, Azure Data Factory, Databricks, or other modern data engineering tools
- Knowledge of data governance, metadata management, cataloging, observability, and cost optimization
- Basic knowledge of Docker, Kubernetes, serverless deployment, or infrastructure as code
- Awareness of AI/GenAI concepts: LLMs, embeddings, semantic search, RAG, prompt-based workflows, AI-ready data preparation
- Willingness to use AI-assisted development tools (GitHub Copilot, Cursor, Claude Code, or similar)
Full description
Job Description:
Join our team of data engineers and analytics specialists building modern data platforms for enterprise-scale reporting, automation, and AI-enabled use cases. In this role, you will work with Snowflake as the core cloud data platform, modern ETL/ELT orchestration tools, and AI-ready data engineering practices to deliver reliable, scalable, and business-oriented data solutions.
For our German client we are currently looking for:
Snowflake Data Engineer with German
Good command of German is required.
Key responsibilities:
- Design, develop, and maintain production-grade ETL/ELT pipelines in Snowflake using SQL, Python, and modern orchestration tools
- Build data models and dbt transformations for reporting and analytics
- Optimize SQL queries and Snowflake warehouse performance, and manage databases, schemas, and access controls to support efficient, secure data processing
- Integrate Snowflake pipelines with cloud storage and services, and contribute to Data Lake and Lakehouse solutions for ingestion, storage, and analytics
- Use Git and CI/CD tools to test, deploy, and document changes
- Cooperate with technical and business teams to understand requirements and deliver solutions, communicating in German
Required skills:
- Several years’ experience (3–5 years) as a Data Engineer, including in-depth practical experience with Snowflake as a data warehouse
- Strong hands-on experience with Snowflake development, including databases, schemas, stages, streams/tasks, views, stored procedures, performance tuning, and access management
- Good understanding of data warehouse design, dimensional modeling, Kimball methodology, data marts, and star/snowflake schemas
- Excellent SQL skills and practical experience designing efficient transformations, analytical queries, and reusable data models
- Experience building production-grade ETL/ELT pipelines with modern orchestration tools
- In-depth experience with dbt (development, testing and deployment of models)
- Good Python skills for data processing, automation, testing, and integration tasks
- Practical understanding of Data Lake and Lakehouse concepts, including ingestion, storage, governance, and analytics enablement
- Practical experience with at least one cloud platform, preferably Azure, AWS, or GCP, including storage, compute, networking, identity, and security basics
- Practical knowledge of Git, Azure DevOps or similar tools, code reviews, testing, and CI/CD practices
- Good communication skills and ability to work with both technical and business stakeholders
- Good command of German (minimum B2)