Roles & Responsibilities
We're seeking a Senior Data Engineer with expertise in building scalable data architectures and real-time data processing systems. You'll design and implement large-scale data pipelines to process unstructured data, driving insights and business value.
Key Responsibilities :
- Design and develop scalable data architectures using Spark Streaming, PySpark, and Scala
- Process and analyze large volumes of unstructured data from various sources
- Build and maintain real-time data pipelines for data integration and analytics
- Collaborate with cross-functional teams to integrate data insights into business applications
- Optimize data processing workflows for performance, reliability, and scalability
- Troubleshoot data pipeline issues and ensure high data quality
Requirements :
10+ years of experience in data engineering, with a focus on building scalable data systemsStrong expertise in Spark Streaming, PySpark, and ScalaExperience working with large-scale unstructured data and real-time data processingProficiency in data processing frameworks and tools (e.g., Apache Spark, Apache Kafka)Strong analytical and problem-solving skills, with attention to detail and scalabilityExcellent communication and collaboration skillsNice to Have :
Experience with machine learning algorithms and model deploymentKnowledge of cloud-based data platforms (e.g., AWS, GCP, Azure)Familiarity with containerization (e.g., Docker) and orchestration (e.g., Kubernetes)What We Offer :
Competitive salary and benefits packageOpportunity to work on complex data engineering projectsCollaborative and dynamic work environmentTell employers what skills you have
Machine Learning
PySpark
Apache Spark
Scalability
Scala
Kubernetes
Azure
Pipelines
Data Integration
Data Quality
Reliability
Data Engineering
Apache Kafka
Docker
GCP
Orchestration