Data Platform Engineer – AWS & Streaming Systems
At Intellibus, we engineer platforms that power some of the world’s leading FinTech and Financial Trading organizations.
Our Platform Engineering Team works on large-scale cloud and data modernization initiatives involving high-volume distributed systems, real-time data movement, cloud-native engineering, and enterprise-scale data platforms.
We are currently looking for strong Data Engineers with deep expertise in SQL, AWS, and Kafka to join high-impact engineering initiatives supporting mission-critical financial platforms.
What We Offer:
A dynamic environment where your skills will make a direct impact. The opportunity to work with cutting-edge technologies and innovative projects. A collaborative team that values your passion and focus.
We are looking for Engineers who can
• 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.
Key Skills & Qualifications:
• 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.
What we are looking for
• 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.
Preferred Experience
• Snowflake.
• Spark / PySpark.
• PostgreSQL.
• Airflow / dbt.
• Data migration initiatives.
• Real-time streaming platforms.
• FinTech, Banking, Trading, or Capital Markets environments.
• Agile engineering teams.
Technologies We Work With
AWS | Kafka | SQL | Snowflake | Python | Java | Spark | PostgreSQL | Airflow | ETL | Data Warehousing | Unix/Linux | Data Modeling | Cloud Engineering | Real-Time Streaming
Compensation $65-70$/Hour
Our Process
• Schedule a 15 min Video Call with someone from our Team
• 4 Proctored GQ Tests (Apply tot his job
Apply To this Job
Our Platform Engineering Team works on large-scale cloud and data modernization initiatives involving high-volume distributed systems, real-time data movement, cloud-native engineering, and enterprise-scale data platforms.
We are currently looking for strong Data Engineers with deep expertise in SQL, AWS, and Kafka to join high-impact engineering initiatives supporting mission-critical financial platforms.
What We Offer:
A dynamic environment where your skills will make a direct impact. The opportunity to work with cutting-edge technologies and innovative projects. A collaborative team that values your passion and focus.
We are looking for Engineers who can
• 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.
Key Skills & Qualifications:
• 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.
What we are looking for
• 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.
Preferred Experience
• Snowflake.
• Spark / PySpark.
• PostgreSQL.
• Airflow / dbt.
• Data migration initiatives.
• Real-time streaming platforms.
• FinTech, Banking, Trading, or Capital Markets environments.
• Agile engineering teams.
Technologies We Work With
AWS | Kafka | SQL | Snowflake | Python | Java | Spark | PostgreSQL | Airflow | ETL | Data Warehousing | Unix/Linux | Data Modeling | Cloud Engineering | Real-Time Streaming
Compensation $65-70$/Hour
Our Process
• Schedule a 15 min Video Call with someone from our Team
• 4 Proctored GQ Tests (Apply tot his job
Apply To this Job