3-6 years of experience in the Data Engineering field.
Strong hands-on experience in Python for data engineering, including building and maintaining production-grade, large-scale data pipelines
Advanced experience with Azure Data Factory and Azure-based data platforms for orchestration, integration, and scalable data processing
Working experience with Microsoft Fabric, including Lakehouse and data engineering workloads, along with a strong understanding of ETL/ELT and data warehousing concepts
Expert-level SQL skills covering complex query development, optimization, indexing, and partitioning for high-performance systems
Proven experience handling large-volume, high-throughput data and distributed processing environment.
Experience with analytics and visualization platforms such as Power BI
Knowledge of Delta Lake, Spark, and distributed data processing frameworks
Experience implementing CI/CD practices for data pipelines and data engineering workflows
Exposure to data governance, lineage, metadata management, and compliance-driven environments such as fintech or high-transaction systems
Hands-on leadership mindset with strong ownership and accountability for outcomes
Ability to mentor, guide, and grow junior engineers while leading by example
Clear and effective communication with technical and non-technical stakeholders
Strong problem-solving, analytical reasoning, and decision-making skills
