Senior Data Engineer
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Job Description
Senior Data Engineer developing Sigma Software’s corporate Data Platform that powers analytics and decision-making. Collaborating closely with teams to enhance data quality and operational insights.
Responsibilities:
- 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
Requirements:
- 5+ years of experience in Data Engineering
- 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
Benefits:
- culture that supports professional growth
- knowledge sharing
- use of modern tools, including AI-assisted engineering
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