Senior Data Engineer (GCP, BigQuery) (вакансія неактивна)

We are hiring a Senior Data Engineer to build, adapt, and maintain the pipelines and data flows required for new data-driven solutions.

This is a hands-on engineering role focused on Python, GCP, BigQuery, and data pipelines, working closely with data scientists and technical leadership. You will support the execution side of the solution by building pipelines, integrating services, and operationalizing data transformations and models.Beyond strong execution, this role also requires the ability to work through ambiguity, align with technical stakeholders, and help translate an evolving project vision into concrete data engineering deliverables. You will help turn partially formed requirements and architecture decisions into reliable, production-ready workflows. That addition comes from the transcript’s emphasis on needing a clearer project explanation and a more direct technical perspective on what is being built.

Must-have for the position

• Strong experience with Python for data engineering
• Strong experience with GCP and cloud-based data workflows
• Experience building and maintaining production data pipelines
• Strong SQL and data modeling skills
• Ability to work with large-scale or unstructured data
• Experience collaborating with data scientists and cross-functional engineering teams
• Ability to build practical, reliable solutions in an evolving environment
• Confidence working in projects where requirements are still being refined
• Ability to align with multiple stakeholders and translate technical direction into execution
• Upper-Intermediate English or higher.

Will be a strong plus

• Experience with DBT
• Experience with Airflow or Cloud Composer
• Experience with large, unstructured, or voice-related datasets
• Lead-level coordination experience
• Experience supporting production data workflows in rapidly evolving projects

Responsibilities

• Build new data pipelines and adapt existing ETL / ELT workflows
• Move and organize data in cloud storage and analytical systems such as BigQuery
• Work closely with data scientists on tables, transformations, and methodology implementation
• Connect services and data sources required for the solution
• Optimize queries and support scalable data processing
• Work with large, unstructured datasets, including voice-related data
• Help operationalize evolving architecture decisions into production-ready data flows
• Collaborate with engineering and data teams to ensure reliable execution
• Translate evolving project requirements into practical engineering tasks
• Work closely with technical leadership to clarify priorities, solution direction, and implementation needs
• Support project alignment by turning high-level concepts into stable, maintainable data workflows

About the project

Our client is building data- and AI-driven solutions in a cloud-first environment, with a strong focus on GCP, BigQuery, and scalable data workflows. Their teams work across data science, engineering, and solution design to create systems that can support large-scale, real-world use cases, including voice-related and unstructured data scenarios.

The environment is collaborative and execution-focused, with data engineers playing a key role in translating architecture and analytical needs into working pipelines and production-ready data flows. This role joins a project that is already in motion and continuing to evolve, so the team is looking for someone who can work effectively in a setting where requirements are still being clarified and solution details continue to mature. That framing reflects the interview transcript’s emphasis on an already-discussed project that still needs clearer internal alignment and explanation.

Tech Stack: Python, SQL, GCP, BigQuery, Data pipelines, ETL / ELT workflows, Data modeling ,DBT.

Working conditions

• Work schedule: Preferably 10:00 — 18:00 UK hours.
• Engagement: full-time.
• Fully Remote: This role offers the flexibility to work from anywhere (Occasional travel to company offices may be required, a few times per year)

Interview process

• HR Interview: Initial discussion with our recruiter;
• KITRUM’s Technical Interview (90 minutes);
• Client Interview (30-minute discussion).

Why you’ll love working here

• Scale & complexity: real high-load systems, real business impact, real production ownership
• Fast delivery culture: multiple releases daily with modern engineering practices
• Growth opportunities: explore new areas (including infrastructure path), learn continuously
• International collaboration: distributed team, broad exposure to product and engineering practices
• Meaningful modernization: improve a mature platform safely, not by risky rewrites

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