Senior Data Engineer (Cloud)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer (Cloud) based in United Kingdom.

This role offers the opportunity to modernize data infrastructure and build scalable cloud-based data products in a globally distributed technology environment.

You will lead the migration of data workloads from legacy SQL Server environments to modern cloud platforms.

Your work will directly improve the reliability, quality, performance, and accessibility of analytical data.

You will design production-grade ETL/ELT pipelines, analytical models, and cloud data workflows using modern engineering practices.

The role combines hands-on data engineering with cloud infrastructure, platform automation, and AI-assisted engineering initiatives.

You will collaborate with analysts, engineers, and business stakeholders to translate complex requirements and legacy logic into robust solutions.

This is an excellent opportunity for a senior engineer who enjoys solving challenging data problems and shaping modern cloud platforms.

Accountabilities

• Migrate data products, analytical workloads, and associated processes from MS SQL Server to a modern cloud data platform.
• Analyze legacy SQL, ETL workflows, data models, and business logic, redesigning them to align with the target cloud architecture.
• Build, maintain, and optimize scalable batch data pipelines and analytical data models for production use.
• Deploy, configure, and operate managed cloud data services, including data warehouses, workflow orchestration, managed compute, and storage.
• Validate migrated data, investigate discrepancies, and implement measures to maintain high standards of data accuracy and quality.
• Collaborate with data analysts and business stakeholders to clarify requirements, understand business logic, and ensure technical solutions support analytical needs.
• Contribute to data platform reliability, performance optimization, cost efficiency, monitoring, and broader engineering best practices.
• Develop and improve AI-assisted engineering automation for data engineering workflows, including reusable agent capabilities, shared specifications, evaluation frameworks, quality controls, and supporting tools.
• Apply automation and infrastructure engineering practices to improve the efficiency, consistency, and scalability of data workflows.
• Identify technical risks and opportunities for continuous improvement across data pipelines, cloud infrastructure, and analytical workloads.

Requirements

• Strong professional background in Data Engineering with advanced SQL skills and extensive experience working with relational databases.
• Hands-on experience with GCP data technologies or another major cloud platform, with strong practical knowledge of services such as BigQuery, Cloud Composer, and Google Cloud Storage.
• Proven experience designing and operating production-grade ETL/ELT pipelines and analytical data models.
• Experience deploying, configuring, and managing cloud data services, including workflow orchestration, managed or serverless compute, analytical warehouses, and cloud storage.
• Strong Python skills or proficiency in another general-purpose programming language, with practical application across data engineering, platform automation, and analytical workloads.
• Solid understanding of cloud infrastructure concepts, including IAM, networking, monitoring, CI/CD, and infrastructure configuration.
• Experience working with legacy data warehouses, complex SQL environments, and business logic that requires careful analysis and modernization.
• Ability to investigate data issues, identify root causes, validate migrations, and maintain strong data quality standards.
• Strong problem-solving and analytical capabilities, combined with a structured and engineering-focused approach to complex technical challenges.
• Comfortable collaborating with technical and non-technical stakeholders in a distributed, international environment.
• Fluent Russian communication skills.

Benefits

• Fully remote, full-time opportunity with the flexibility to work from anywhere.
• Initial compensation or salary range shared with candidates during the recruitment process before employment begins.
• 28 calendar days of vacation per year.
• 7 wellness days annually for personal, household, or recovery needs.
• Referral bonuses of up to $5,000 for successful candidate recommendations.
• 50% reimbursement for professional training, international conferences, and industry events.
• Corporate discounts for English-language lessons.
• Health support, including reimbursement of up to $1,000 gross per year per employee for eligible employees who do not have access to corporate medical insurance, usable toward health insurance or eligible medical expenses for the employee and close relatives.
• Workplace support, including equipment and workspace resources where available, or reimbursement of up to $1,000 gross every three years toward coworking or home-office costs in other locations.
• Internal gamified recognition program where colleagues can award bonuses that can be exchanged for merchandise, team-building activities, massage certificates, and other benefits.
• Opportunity to work with modern cloud data technologies, AI-assisted engineering automation, and globally distributed technical teams.