We are considering only candidates who are located in Poland.

Client

Our client is a leading AI‑powered workforce transformation and talent management platform.

Position overview

We are seeking a Senior Data Engineer / Team Lead to join a rapidly growing data organization powering an AI-driven HR technology platform used by enterprise customers worldwide.

This is a hands-on senior engineering role focused on building, operating, and evolving a modern data platform leveraging Google BigQuery and Kubernetes-based services. The position blends data engineering, analytics enablement, and platform ownership to deliver reliable, scalable, and high-quality data solutions used across internal teams and customer-facing analytics products.

The successful candidate will collaborate closely with product, engineering, and analytics teams to build robust data pipelines, enable reporting capabilities, and contribute to technical best practices and platform evolution. During an initial transition period, the role may also include technical leadership responsibilities until a dedicated Engineering Manager joins.

Responsibilities

• Design, build, and maintain scalable data pipelines using modern ELT practices.

• Develop and optimize data models within BigQuery and ensure performance, reliability, and cost efficiency.

• Operate and enhance Kubernetes‑based data services as part of the data platform.

• Build clean, reusable datasets to support analytics and reporting needs.

• Support the development of customer‑facing dashboards and analytics features.

• Define and maintain core business metrics and the associated data transformations.

• Enable self‑service data access for internal teams across the organization.

• Implement monitoring, alerting, and observability for all data workflows and pipelines.

• Ensure data correctness, consistency, and overall operational stability.

• Troubleshoot production data issues and drive improvements to system resilience.

• Provide technical guidance and mentorship to engineers during the transition period.

• Participate in design discussions, architecture decisions, and engineering best practices.

• Collaborate closely with product, analytics, and engineering teams to deliver scalable solutions.

• Translate business requirements into well‑designed technical implementations.

• Contribute to continuous improvements in development workflows and team processes.

Requirements

• Strong experience with SQL and data modeling.

• Hands-on experience with Google BigQuery or comparable cloud data warehouses.

• Proven ability to build and operate data pipelines in production environments.

• Programming proficiency in Python, Java, or Node.js.

• Experience working with containerized environments, including Docker and Kubernetes.

• Solid understanding of modern ELT workflows and analytics engineering practices.

• Experience using dbt or similar data transformation frameworks.

• Background supporting customer-facing analytics products.

• Exposure to AI and machine learning data workflows.

• Experience implementing monitoring and alerting for production systems.

• Familiarity with Infrastructure as Code concepts, such as Terraform.

• Strong systems design capabilities and problem‑solving skills.

• Experience working in cloud-native engineering environments.

• Ability to clearly communicate technical concepts to cross-functional stakeholders.

• Comfortable operating in fast-paced product-driven environments.

• Strong ownership mindset with the ability to work autonomously.