Data Engineer

Our Journey So Far

At Snapp, we’re redefining how cities move. Our ride-hailing and mobility platform connects millions of riders and drivers every day, delivering safe, reliable, and efficient transport solutions. Powered by real-time data and robust infrastructure, we make urban travel faster, simpler, and more sustainable.
We operate with the mindset of a global tech leader and the agility of a startup, building services that scale across markets while staying responsive to local needs.


Your Impact

As a Data Engineer, you will design, build, and maintain scalable data infrastructure and pipelines that handle billions of records each day. You will ensure fast, reliable, and high-quality data flows across our lakehouse platform, supporting both streaming and batch processing. Your work will be essential in enabling dependable data access, powering analytics, and accelerating AI-driven initiatives across the organization.

 

What You’ll Drive Forward

● Design and maintain large-scale ETL/ELT pipelines in Apache Flink, Ariflow and Spark for both streaming and batch workloads.
 ● Build and optimize real-time streaming systems using Kafka.
 ● Develop scalable ingestion frameworks for Delta Lake, Iceberg, and Hudi.
 ● Manage and optimize Ceph-based object storage within our data lakehouse.
 ● Oversee ClickHouse operations to ensure high-performance analytical querying.
 ● Drive reliability, scalability, and cost efficiency across systems handling billions of daily records.
 ● Deliver production-grade code in Python, Go, or Java.
 ● Implement data quality, monitoring, and observability frameworks.
 ● Collaborate with ML/AI teams to support model training, feature pipelines, and inference workflows.
 ● Reduce data pipeline latency by implementing efficient streaming architectures.
 ● Optimize storage costs while maintaining query performance across lakehouse layers.
 

What Powers Your Drive

 ● 3-5 years of experience in data engineering roles.
 ● Strong proficiency in at least two programming languages: Python, Go, or Java.
 ● Hands-on experience with Kafka and stream processing (Flink or Spark Streaming).
 ● Solid understanding of Spark and distributed computing.
 ● Experience with at least one lakehouse table format (Delta Lake, Iceberg, or Hudi).
 ● Strong SQL skills and experience with analytical databases (ClickHouse or similar columnar databases).
 ● Strong understanding of data modeling, data warehousing concepts, and ETL best practices
 ● Experience with version control (Git) and CI/CD practices.
 ● Strong problem-solving abilities and analytical thinking.
 ● Excellent collaboration and communication skills.
 ● Adaptability to rapidly evolving technology landscape.
 

Ready to Get on Board?

Help us shape the future of ride-hailing and urban mobility. Submit your CV and let’s build smarter cities together.