Data Engineer – Kafka & Cloud Data Pipelines

Intellibus engineers platforms that power leading FinTech and Financial Trading organizations. They are seeking strong Data Engineers with expertise in SQL, AWS, and Kafka to support mission-critical financial platforms through high-impact engineering initiatives.

Responsibilities:

• Build scalable cloud-native data platforms on AWS
• Design and optimize large-scale ETL/ELT pipelines
• Develop real-time and batch data processing systems using Kafka and distributed data technologies
• Engineer high-performance SQL-based data solutions for enterprise-scale workloads
• Work on data ingestion, transformation, migration, and warehousing initiatives
• Partner closely with engineering, platform, and business teams to solve complex data challenges
• Improve reliability, observability, scalability, and operational excellence across the data ecosystem
• Contribute to cloud modernization and platform engineering efforts in fast-paced FinTech environments

Requirements:

• Strong SQL expertise (advanced querying, optimization, performance tuning)
• Hands-on AWS engineering experience
• Strong Kafka / event-driven systems experience
• Experience building scalable ETL/ELT pipelines
• Python or Java programming experience
• Experience with data warehousing and distributed data systems
• Strong understanding of cloud-native data architecture
• 10+ years of Data Engineering experience
• Strong ownership mindset and problem-solving ability
• Experience working on large-scale enterprise data platforms
• Ability to work in fast-moving engineering environments
• Strong communication and collaboration skills
• Experience supporting production-grade systems and mission-critical workloads
• Snowflake
• Spark / PySpark
• PostgreSQL
• Airflow / dbt
• Data migration initiatives
• Real-time streaming platforms
• FinTech, Banking, Trading, or Capital Markets environments
• Agile engineering teams