Cloud Data Engineer

SIX; Warszawa; On-site; PLN 180,000 - 260,000; Full time

Job summary

SIX is building a company-wide cloud-native data platform to serve analytics and data science across the organization. You will join an international team responsible for designing and implementing reliable data capabilities and providing consulting to internal customers.

The role emphasizes hands-on data engineering, scalable ETL pipelines, ML/AI use cases, and ongoing platform improvement through IaC and standardized templates.

Qualifications

• 4+ years of practical experience building production data pipelines, data modeling and BI tools in the cloud.
• Lakehouse architecture experience, preferably Databricks, with Spark and Delta/Iceberg formats.
• Proficiency with Python (PySpark) and SQL, plus CI/CD to build production data and ML pipelines.

Responsibilities

• Design and maintain a mature cloud-native data science platform used by 14+ internal analytics teams and 600+ users.
• Collaborate with business data science and IT data engineering stakeholders to enable platform usage.
• Identify requirements, analyze platform suitability, and propose best practices with demos.
• Onboard new use cases and optimize pipelines, ML/AI use cases, and reporting solutions.
• Implement infrastructure components with IaC and create templates to standardize analytics teams.

Skills

Data pipelines

Data modeling

BI tools

Databricks

Spark

Python (PySpark)

SQL

CI/CD

IaC

Terraform

Tools

Databricks

Terraform

Pulumi

OpenTable formats

Job description

SIX is recruiting a data platform engineer to work on the company wide data platform. In this role, you will be part of a cross-functional team responsible for both designing and implementing a reliable platform for analytics and data science, as well as consulting internal customers who use the platform across the organization.

What You Will Do

• Be part of an international team that designs and maintains a mature cloud native data science platform, currently serving more than 14 internal analytics teams and 600+ users.
• Closely collaborate with key stakeholders from business data science teams and IT data engineering teams to enable them on the platform.
• Identify new requirements, analyze platform suitability, propose best practices and existing solutions through demos.
• Act as a hands-on data engineer to onboard new use cases and optimize existing ones by building production-ready ETL pipelines, ML/AI use cases and reporting solutions.
• Implement new infrastructure components with Infrastructure as code (IaC), as well as creating templates to ensure best practices and standardization among analytics teams.

What You Bring

• 4+ years of practical experience building production data pipelines, data modeling and BI tools in the cloud.
• Experience with Lakehouse architecture, preferably Databricks, with a strong knowledge of Spark and Open Table formats (Delta and/or Iceberg).
• Proficiency with Python (PySpark) and SQL with a solid understanding of software development and automation concepts like CI/CD to build production data and ML pipelines (DataOps/MLOps).
• Basic knowledge of cloud foundation services (IAM, networking, storage...), cloud costs management (FinOps) as well as tools to manage cloud infrastructure with IaC (Terraform/OpenTofu, Pulumi, bash scripting...) on Microsoft Azure (our primary cloud service provider) and/or Amazon Web Services, Google Cloud Platform.
• Growth mindset and a very proactive attitude for continuous learning and development.
• Good presentation and communication skills.
• Fluency in written and spoken English.