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
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