Hybrid Senior Data Engineer: Scale Data Pipelines

WPP Media; Warszawa; Hybrid; PLN 95,000 - 190,000; Full time

Job summary

WPP in Warsaw is seeking a Senior Data Engineer to build scalable data platforms powering Open Intelligence products. You will design and maintain data pipelines, ETL/ELT workflows, data models, and storage solutions for large-scale datasets, collaborating with engineering, analytics, and product teams to deliver robust data solutions.

The role emphasizes reliability, observability, and governance across distributed systems, with cloud-native tooling (GCP, Kubernetes, Terraform) and a focus on

Qualifications

• Strong communication skills to explain technical concepts clearly.
• 4+ years in data engineering.
• Proficient wrangling data with Python/Go/Scala.
• Experience with Spark and large-scale processing.
• Familiarity with CI/CD, GCP, and IaC tooling.

Responsibilities

• Design, build, and maintain scalable data pipelines and processing frameworks.
• Develop reliable ETL/ELT workflows for analytics and operations.
• Model data, optimize storage, and enable large-scale integration.
• Collaborate with software engineering, analytics, product, and platform teams.
• Improve data quality, observability, reliability, and performance.
• Support real-time and batch processing using cloud-native tech.
• Contribute to data platform architecture and best practices.
• Implement monitoring, testing, and automation to reduce failures.
• Troubleshoot distributed data and infrastructure issues.
• Promote governance, security, and compliance in data environments.
• Mentor junior engineers and foster collaborative culture.
• Evaluate new tools and technologies to boost scalability.

Skills

Data engineering

Python/Go/Scala

Spark

CI/CD

GCP

Communication

Tools

Kubernetes

Terraform

Job description

WPP in Warsaw is seeking a Senior Data Engineer to build scalable data platforms powering Open Intelligence products. You will design and maintain data pipelines, ETL/ELT workflows, data models, and storage solutions for large-scale datasets, collaborating with engineering, analytics, and product teams to deliver robust data solutions.

The role emphasizes reliability, observability, and governance across distributed systems, with cloud-native tooling (GCP, Kubernetes, Terraform) and a focus on