Senior Data Engineer

• 5+ years of experience in Data Engineering and Data Warehousing within large-scale enterprise environments
• Proven ability to design scalable, maintainable, and modern data warehouse solutions
• Hands-on experience with Snowflake, dbt, Airflow
• Solid understanding of modern data engineering practices, CI/CD pipelines, and orchestration frameworks
• Experience taking full ownership from requirements analysis to production delivery
• Strong analytical mindset and ability to proactively clarify business requirements
• Experience building robust, maintainable, and high-quality data solutions
• Understanding of data modeling principles and modern data architecture approaches
• Strong communication and stakeholder management skills
• Interest in leveraging AI-driven development tools and automation to improve engineering efficiency

As a recruitment company, DCG understands that every business is powered by experienced professionals. Our management style and partnership approach enable us to meet your needs and provide continuous support. Due to our ongoing growth and the large number of recruitment projects we undertake for our partners, we are currently looking for:

Senior Data Engineer

Offer:

• Private medical care
• Co-financing for the sports card
• Constant support of dedicated consultant
• Employee referral program

,[Support the foundational phase of a new data engineering team and help transform business challenges into scalable data solutions, Design and build modern data models, pipelines, and data warehouse solutions end-to-end, Drive modernization initiatives by transitioning fragmented local systems into unified enterprise-grade solutions, Collaborate closely with business stakeholders, architects, and engineering teams to ensure alignment throughout the development lifecycle, Take ownership of the full delivery lifecycle - from requirements gathering and solution design to implementation, testing, and production deployment, Promote engineering best practices, including clean architecture, design patterns, CI/CD, and Test-Driven Development (TDD), Ensure high standards of reliability, maintainability, scalability, and data quality, Drive adoption of AI-assisted engineering practices and tools such as GitHub Copilot and internal AI agents to improve engineering productivity] Requirements: Data engineering, Data warehouse, Snowflake, dbt, CD pipelines, Requirements analysis, Stakeholder management Additionally: Private healthcare, Sport subscription.