Senior Data Engineer

• Collaborate with business stakeholders and technical teams to understand and analyze data requirements
• Lead the design and implementation of data models and database structures that meet business needs
• Profile, refactor, and tune performance in the database
• Design and implement complex ETL processes to extract, transform, and load data from various source systems into the data warehouse
• Ensure data integrity, consistency, and accuracy through robust data quality assurance measures
• Review and support team members, providing guidance and mentorship
• Supervise and contribute to the data-driven strategy for the project, aligning it with business objectives

Tech Stack:

• Python
• Kafka
• Apache Flink / Apache Spark (Streaming)
• Apache Hudi / Apache Iceberg 

Required skills:

• 5+ years of experience as a Data Engineer or similar role, with hands-on expertise in large-scale, production-grade data pipelines.
• 3+ years of experience designing and running real-time data streaming systems (Kafka + Flink / Spark Streaming).
• 3+ years of proficiency in Python for data engineering (data processing, orchestration, automation).
• Solid understanding of distributed systems, data partitioning, checkpointing, and fault-tolerant stream processing.
• Practical experience with Apache Hudi or Apache Iceberg for incremental data storage and schema evolution.
• Experience with RDBMS sources (PostgreSQL, MySQL, etc.) and data lakes / object storage (S3, GCS, etc.).
• Deep understanding of ETL / ELT design patterns, data modeling, and data quality principles.
• Experience deploying and maintaining data infrastructure in cloud environments (AWS / GCP / Azure).
• Excellent analytical and problem-solving skills, with the ability to design robust, scalable, and efficient architectures.
• Strong communication skills and ability to collaborate with cross-functional teams.