Posted on: 23/01/2026
Description :
- Own end-to-end technical design and architecture of batch and streaming data pipelines
- Lead development of high-throughput, low-latency data processing systems using Java
- Design and implement real-time streaming solutions (event ingestion, processing, aggregation)
- Drive code quality, performance optimization, and scalability across systems
- Review code, mentor engineers, and set engineering best practices
- Collaborate with product, platform, infra, and security teams to deliver production-grade solutions
- Ensure data reliability, fault tolerance, and observability (metrics, logs, alerts)
- Automate operational workflows and deployment pipelines
- Participate in capacity planning, cost optimization, and system tuning
- Stay current with evolving Big Data and streaming ecosystems and evaluate new technologies
Required Skills & Experience :
Core Technical Skills :
- Strong proficiency in Java (multithreading, concurrency, JVM tuning)
- Hands-on experience with distributed data processing frameworks :
1. Apache Spark (Core, SQL, Streaming / Structured Streaming / Apache Flink)
2. Apache Kafka (producers, consumers, partitions, offsets, exactly-once semantics)
- Solid understanding of batch + streaming architectures (Lambda / Kappa patterns)
- Experience with Hadoop ecosystem components (HDFS, Hive, YARN or equivalents)
Data & Storage :
- Strong knowledge of relational databases (PostgreSQL, MySQL)
- Experience with NoSQL / distributed datastores (HBase, Cassandra, MongoDB, Pinot etc.)
- Understanding of data modeling, partitioning, and schema evolution
Platform & Operations :
- Experience with Linux-based systems and production deployments
- Exposure to containerization and orchestration (Docker, Kubernetes preferred)
- Familiarity with monitoring and observability tools (Grafana, Prometheus, ELK, etc.)
- Experience with CI/CD pipelines and automated testing frameworks
Leadership & Soft Skills :
- Proven experience leading technical teams and driving delivery
- Strong problem-solving and debugging skills in complex distributed systems
- Ability to take ownership of critical systems and make architectural decisions
- Excellent communication skills to work with cross-functional stakeholders
- Comfortable working in a fast-paced, evolving data ecosystem
Good to Have (Plus Skills) :
- Experience with Flink / Kafka Streams / real-time analytics
- Exposure to cloud-native data platforms (AWS, GCP, Azure)
- Knowledge of data governance, security, and access control
- Experience in telecom, fintech, or large-scale consumer data platforms
Why This Role :
- Work on large-scale, real-time data systems
- High technical ownership and architectural influence
- Opportunity to shape next-generation streaming and analytics platforms
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Posted in
Data Engineering
Functional Area
Data Engineering
Job Code
1605149