Data Engineer ID52278

• What you will do
• Design, build, and optimize high-volume, high-performance ELT pipelines for a centralized data warehouse;
• Collaborate with Product, ML Engineers, Data Scientists, and DevOps to define scalable and secure data platform architecture;
• Own key data warehouse components including development, deployment, monitoring, and continuous improvement;
• Provide technical leadership through data architecture reviews and system design discussions;
• Contribute to engineering culture and data-driven best practices;
• Support internal and external stakeholders with a focus on data accessibility and usability;
• Mentor team members and participate in hiring processes.

• Must haves
• 5+ years of experience in data engineering building scalable systems and pipelines;
• Expert proficiency in SQL and strong coding skills in Python ;
• Hands-on experience with data warehousing, data lakes, and large-scale data systems ;
• Strong understanding of computer science fundamentals (data structures, algorithms, distributed systems) ;
• Solid understanding of distributed system architecture focusing on availability, reliability, and performance;
• Strong focus on execution and product delivery;
• Exceptional attention to detail and quality;
• Strong communication skills;
• Ability to mentor and support other engineers;
• Leadership mindset with ability to take initiative and deliver results;
• Comfort working in a fast-paced, evolving environment;
• Familiarity with Python, Django, Kubernetes, PostgreSQL, DBT, Redshift, AWS ;
• Upper-intermediate English level.

As a Data Engineer , you will design and scale high-performance ELT pipelines that power a centralized data warehouse and enable reliable, data-driven decision-making across the organization. You’ll collaborate closely with cross‑functional teams to build a robust, scalable data platform, ensuring data quality, accessibility, and performance. This role offers strong ownership, architectural influence, and the opportunity to shape data systems, best practices, and a growing data‑driven culture.

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