We’re looking for a Data Platform Engineer to help architect and maintain a modern, scalable data platform that supports real-time and batch AI workloads. You will work on building a unified data lakehouse architecture using cutting-edge tools like Kafka, Apache Hudi, and cloud-native storage systems.
You’ll collaborate closely with AI engineers, backend developers, and infrastructure teams to ensure our platform has fast, reliable, and traceable access to structured and semi-structured data.
Requirements
- 4+ years of experience in data engineering or data infrastructure roles
- Strong experience with Apache Kafka in production environments
- Hands-on experience with Apache Hudi, Delta Lake, or similar lakehouse frameworks
- Deep understanding of data lake architecture, partitioning, file formats (e.g., Parquet), and cloud object storage (e.g., AWS S3)
- Proficiency in Python, Scala, or Java for data processing
- Experience building pipelines using Apache Spark, Flink, or similar frameworks
Nice to Have
- Experience with streaming ETL, CDC pipelines, or event-driven architectures
- Experience in a DevOps or cloud-native environment (e.g., Kubernetes, Terraform, CI/CD)
Key Responsibilities
- Design and implement scalable, fault-tolerant data pipelines for streaming and batch workloads
- Build and optimize a Lakehouse architecture using tools like Apache Hudi and AWS S3
- Integrate Kafka for real-time event ingestion and processing
Manage schema evolution, metadata consistency, and partitioning strategies for large datasets - Collaborate with platform, AI, and analytics teams to define data models and access patterns
- Ensure data quality, lineage, and governance across systems
About Emumba
We specialize in delivering innovative solutions and exceptional services to meet the diverse needs of our clients. With a strong commitment to quality and customer satisfaction, we strive to exceed expectations and drive success in every project we undertake.
Application Deadline
September 17, 2025
Department
Backend
Employment Type
Full Time
Location
Islamabad, Pak
Workplace type
Hybrid
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