We are looking for an experienced Data Engineer with solid expertise in real-time data streaming and distributed data processing technologies. The ideal candidate should have hands-on experience in building scalable, event-driven data platforms using Apache Flink, Kafka, Java/Scala, and PySpark. The candidate will be responsible for designing, developing, and maintaining high-performance data engineering solutions within large-scale enterprise environments.

Requirements

Key Responsibilities:

- Design, develop, and maintain real-time streaming data pipelines and event-driven architectures.
- Build scalable and fault-tolerant data engineering solutions using Apache Flink, Kafka, and Java/Scala.
- Develop and optimize distributed data processing applications for enterprise-grade systems.
- Implement best practices for performance tuning, resiliency, security, and compliance requirements.
- Collaborate with cross-functional teams to design technical and application architectures.
- Ensure production-grade monitoring, troubleshooting, and operational excellence of distributed services.
- Contribute to CI/CD implementation and DevOps best practices.
- Work closely with engineering teams to drive technical improvements and architectural decisions.

Mandatory Technical Skills:

- Minimum 4+ years of development and design experience in:
- - Apache Flink
- Java or Scala
- Apache Kafka
- PySpark
- Real-time data streaming technologies
- Event-driven architectures

- Hands-on experience with:
- - Apache Flink (Beam or Spark Streaming experience is also valuable)
- Kafka ecosystem and streaming platforms
- JVM tuning and performance optimization
- Distributed systems design and implementation
- Docker and Kubernetes containerization
- Linux OS administration and Shell scripting
- SQL and NoSQL databases
- CI/CD tools such as GitHub and Jenkins
- Design patterns and their implementation




- Production monitoring and troubleshooting of distributed services

Nice to Have Skills:

- Redis or other caching technologies.
- Experience with Spark Streaming or Apache Beam.
- Experience working with banking or fintech platforms.

Data Engineering & Security Requirements:

- Strong understanding of data security principles and controls.
- Experience implementing secure data transfer mechanisms including:
- - CRON jobs
- ETL processes
- JDBC and ODBC scripts

- Knowledge of encryption, anonymization, data integrity, and policy controls in large-scale infrastructures.
- Understanding of data sensitivity requirements, including:
- - Protection of PII data
- Secure logging practices
- Secure in-memory data handling

- Ability to identify security design gaps and recommend enhancements.
- Experience implementing wrapper solutions for legacy or third-party components to ensure compliance requirements are met.

Infrastructure & Networking Knowledge:

- Working knowledge of:
- - DNS
- Proxy servers
- ACLs
- Networking policies
- Troubleshooting network-related issues

Functional Requirements:

- Experience working in Agile environments.
- Ability to design and implement scalable technical architectures.
- Conduct technology research and benchmarking activities.
- Ability to influence engineering teams on technical best practices.
- Experience working in enterprise-scale environments.
- Banking, Financial Services, or FinTech domain experience is preferred.

Soft Skills:

- Excellent communication and interpersonal skills.
- Strong problem-solving and analytical abilities.
- Self-driven and capable of working independently.
- Ability to collaborate effectively with cross-functional teams and stakeholders.
- Strong presentation and listening skills.
- Positive attitude and ability to foster a collaborative team environment.
- Passionate about engineering excellence and continuous improvement.

📌 Senior Data Engineer - (Flink/Kafka/PySpark) (India)
🏢 GSSTech Group
📍 India