About Mozn
MOZN is a leading Enterprise AI company enabling organizations to make informed decisions in two critical domains: Financial Crime Prevention and Enterprise Knowledge Intelligence.
We’re a diverse, collaborative team of innovators united by a shared purpose: to build AI that delivers tangible business value, builds trust, and empowers people and organizations with augmented intelligence. Our culture is built on the relentless pursuit of excellence and meaningful impact.
If you’re passionate about working alongside exceptional talent on world-class AI, and you want the autonomy and runway to do the best work of your career, join us in shaping the future of intelligent enterprises.
About the role
We are looking for a highly motivatedData Platform Engineer IIIto join our Cloud Engineering team. The ideal candidate is passionate about building andoperatingmodern data platforms that power analytics, real-time data processing, and AI workloads.
This role focuses on designing, operating, automating, and continuously improving large-scale data infrastructure includingMySQL, PostgreSQL, Kafka, ETL/ELT pipelines, CDC platforms, analytical databases (StarRocks, ClickHouse), and distributed data processing frameworks such as Flink or Sparkacross cloud-native and hybrid environments.
The ideal candidate will possess deep expertise in data engineering platforms and distributed data systems. Kubernetes and cloud platform experience are important, but the primary focus is on enabling scalable, reliable, and high-performance data platforms that support engineering, analytics, and data science teams.
What you'll do
Data Platform Engineering
- Design, deploy, operate, and optimize large-scale data platforms supporting transactional and analytical workloads.
- Build and maintain reliable batch and real-time ETL/ELT pipelines.
- Design and operate CDC platforms using Debezium, Kafka Connect, or similar technologies.
- Deploy, operate, and optimize analytical databases such as StarRocks, ClickHouse, Apache Doris, or similar OLAP platforms.
- Design scalable Kafka architectures, including topics, partitions, replication, consumer groups, and streaming pipelines.
- Administer MySQL and PostgreSQL clusters, including replication, backup, recovery, disaster recovery, and performance tuning.
- Optimize distributed query performance, storage layouts, indexing strategies, and data lifecycle management.
- Support large-scale ingestion, transformation, and analytical workloads while ensuring platform reliability and scalability.
Distributed Data Systems - Design and operate streaming and real-time data platforms using Kafka, Flink, Spark, or similar technologies.
- Optimize distributed systems for throughput, latency, scalability, and resilience.
- Troubleshoot complex issues across distributed databases, messaging systems, and data processing pipelines.
- Collaborate closely with Data Engineering, Analytics, and Data Science teams to build reliable data platform capabilities.
Platform Automation - Automate provisioning, deployment, upgrades, scaling, and lifecycle management of data platforms.
- Build self-service capabilities for engineering teams.
- Improve observability, monitoring, reliability, and operational excellence across the data platform.
Qualifications
- 4-7years of experience in Data Platform Engineering, Database Engineering, Platform Engineering, or Data Infrastructure.
- Strong production experience with MySQL and PostgreSQL.
- Deep expertise operating Kafka in production environments.
- Strong experience building ETL/ELT pipelines.
- Hands-on experience with StarRocks, ClickHouse, Apache Doris, or similar OLAP databases.
- Experience with streaming platforms such as Kafka, Flink, Spark Streaming, or Kafka Streams.
- Strong SQL optimization and database performance tuning experience.
- Experience with CDC technologies such as Debezium or Kafka Connect.
- Kubernetes experience deploying and operating stateful data workloads.
- Experience with AWS, GCP, OCI, or Azure.
- Experience with Terraform, Helm, GitOps, and automation frameworks.
- Strong scripting skills in Python, Bash, or Go.
- Experience with observability platforms such as Prometheus, Grafana, ELK/OpenSearch, or LGTM.
Preferred Qualifications
- Experience with Apache Iceberg, Delta Lake, or Apache Hudi.
- Experience with Trino, Presto, Pinot, or Druid.
- Experience supporting Data Science and Analytics platforms.
- Experience designing modern data lakehouse architectures.
- Contributions to open-source data platform technologies.
- Cloud, Kubernetes, Kafka, or Database certifications are a plus.
Benefits
- You will be at the forefront of an exciting time for the Middle East, joining a high-growth rocket-ship in an exciting space
- You will be given a lot of responsibility and trust. We believe that the best results come when the people responsible for a function are given the freedom to do what they think is best
- The fundamentals will be taken care of: competitive compensation, top-tier health insurance, and an enabling culture so that you can focus on what you do best
- You will enjoy a fun and dynamic workplace working alongside some of the greatest minds in AI
- We believe strength lies in difference, embracing all for who they are and empowered to be the best version of themselves
