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 (< 2 hours)
- 30-45 min Final Video Interview
- Receive Job Offer
If you are interested in reaching out to us, please apply, and our team will contact you within the hour. Apply tot his job Apply To this Job