Senior Data Engineer

This is a fully remote position, open to applicants in Ukraine.

📋 Description

• Design, develop, and enhance Data Warehouses, Data Marts, and enterprise data models to facilitate analytics and informed business decisions.

• Create, implement, and optimize scalable ELT pipelines and data processing solutions, ensuring they are reliable, performant, and maintainable.

• Lead technical choices concerning data architecture, platform advancement, data modeling methodologies, and integration strategies.

• Establish and uphold data governance practices, metadata standards, data lineage, security measures, and access management policies.

• Guarantee data quality, observability, monitoring, and operational excellence across the data platform.

• Assess and integrate technologies, tools, and best practices that enhance platform scalability, efficiency, and maintainability.

• Support and improve self-service analytics capabilities utilizing Apache Superset and other BI solutions.

• Work closely with BI Engineers, Business Analysts, and business stakeholders to synchronize data platform capabilities with organizational objectives.

• Mentor Data Engineers, perform technical reviews, and advocate for engineering best practices within the team.

• Utilize AI-assisted engineering techniques to enhance development efficiency, delivery quality, and platform sustainability.

⛳️ Requirements

• Over 5 years of experience in Data Engineering.

• Proficient in SQL, Python, relational databases, and data modeling techniques applicable to Data Warehouses and Data Marts.

• Practical experience in designing and implementing enterprise-scale ELT pipelines and data processing solutions.

• Deep understanding of data architecture, data warehousing, dimensional modeling, and analytical data platforms.

• Familiarity with orchestration and workflow management tools such as Dagster, Airflow, or similar solutions.

• Strong knowledge of data governance, metadata management, data lineage, security, and access control frameworks.

• Experience in 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.

• Familiarity with analytical databases and performance optimization techniques (e.g., ClickHouse or similar technologies).

• Strong grasp 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 contemporary data platform strategies.

• Proficient in AI-assisted engineering practices and practical experience utilizing AI tools to enhance development efficiency and solution quality.

• Excellent communication skills and the ability to collaborate effectively with both technical and non-technical stakeholders.

• Intermediate English proficiency or higher.

🏝️ Benefits

• A culture that fosters professional growth.

• Opportunities for knowledge sharing.

• Utilization of modern tools, including AI-assisted engineering.