What We Need:

• 4+ years of experience as a Data Engineer
• 4+ years of direct experience with SQL (e.g., Redshift/Postgres/MySQL, Snowflake), data modeling, data warehousing, and building ELT/ETL pipelines - MUST
• 2+ years of Python
• 3+ years of experience in scalable data architecture, fault-tolerant ETL, and monitoring of data quality in the cloud
• Experience working with cloud environments (AWS preferred) and big data technologies (EMR, EC2, S3, Snowflake, spark-streaming, DBT, Airflow)
• Exceptional troubleshooting and problem-solving abilities, debugging, and root-causing defects in large-scale systems.
• Deep understanding of distributed data processing architecture and tools such as Kafka, Spark, and Airflow
• Experience with design patterns and coding best practices, understanding of data modeling concepts, techniques, and best practices
• Proficiency with modern source control systems, especially Git
• Basic Linux/Unix system administration skills

Nice to have

• BS or MS degree in Computer Science or a related technical field - An advantage
• Experience with data warehouses
• NoSQL, Large scale DBs.
• Understanding fintech business processes
• DataOps - AWS.
• Microservices
• Experience in DBT

What Else

• Energetic and Data enthusiastic
• Analytical
• Self-motivated and work well both independently and as part of a team
• Excellent verbal/written communication & data presentation skills, including experience communicating with business and technical teams.
• You are a team player with solid communication skills.
• Love to explore new technologies and Fast and self-learner: you can quickly master concepts, disciplines, and methods.