Senior Data Engineer

Job Description

• Design, build, and evolve Data Warehouses, Data Marts, and enterprise data models to support analytics and business decision-making
• Design, implement, and optimize scalable ELT pipelines and data processing solutions, ensuring reliability, performance, and maintainability
• Drive technical decisions related to data architecture, platform evolution, data modeling approaches, and integration patterns
• Establish and maintain data governance practices, metadata standards, data lineage, security controls, and access management policies
• Ensure data quality, observability, monitoring, and operational excellence across the data platform
• Evaluate and introduce technologies, tools, and best practices that improve platform scalability, efficiency, and maintainability
• Support and enhance self-service analytics capabilities through Apache Superset and other BI solutions
• Collaborate closely with BI Engineers, Business Analysts, and business stakeholders to align data platform capabilities with organizational goals
• Mentor Data Engineers, conduct technical reviews, and promote engineering best practices across the team
• Apply AI-assisted engineering practices to improve development efficiency, delivery quality, and platform sustainability

Qualifications

• 5+ years of experience in Data Engineering with a proven track record of delivering complex data platform and analytics solutions
• Strong expertise in SQL, Python, relational databases, and data modeling techniques for Data Warehouses and Data Marts
• Hands-on experience designing and implementing enterprise-scale ELT pipelines and data processing solutions
• Strong understanding of data architecture, data warehousing, dimensional modeling, and analytical data platforms
• Experience with orchestration and workflow management tools such as Dagster, Airflow, or similar platforms
• Strong knowledge of data governance, metadata management, data lineage, security, and access control models
• Experience designing and optimizing analytical workloads, reporting systems, and self-service analytics platforms
• Understanding of data quality management, monitoring, observability, and operational best practices for data platforms
• Experience with analytical databases and performance optimization techniques (e.g., ClickHouse or similar technologies)
• Strong knowledge of database fundamentals, including indexing, normalization, transactions, and query optimization
• Hands-on experience in database development, data modeling, and analytical system design
• Solid understanding of enterprise data architecture principles and modern data platform approaches
• Strong AI-assisted engineering skills and practical experience using AI tools to improve development efficiency and solution quality
• Strong communication skills and ability to collaborate effectively with technical and non-technical stakeholders
• Intermediate English or higher

WILL BE A PLUS

• Experience with Apache Superset, Power BI, or other BI and visualization platforms
• Experience with real-time or event-driven data processing solutions
• Experience building internal data platforms and self-service analytics capabilities
• Experience leading engineering teams or acting as a technical lead

Additional Information

PERSONAL PROFILE

• Proactive and ownership-driven mindset with a focus on long-term platform sustainability
• Strong analytical and problem-solving skills with attention to detail and data quality
• Ability to communicate complex technical concepts in a clear and structured way
• Collaborative team player comfortable working with cross-functional stakeholders
• Continuous learner interested in modern data engineering practices and AI-assisted development