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Data Platform Engineer – AWS & Streaming Systems

Remote · Canada Full-time

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.

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