Flink Developer

Naviq; Thiruvananthapuram; On-site; INR 850,000 - 1,400,000; Full time

Job summary

Naviq is seeking a highly skilled Flink Java Developer to build real-time streaming applications at scale. You will design and implement stateful stream processing using Flink (Java), with strong emphasis on event-time processing, watermarks, and windowing.

The role requires solid Kafka expertise and performance tuning in complex data pipelines. You will work across cloud-native deployments, ensure fault tolerance, and optimize end-to-end streaming throughput.

Qualifications

• 3–8 years hands-on Apache Flink experience in Java development.
• Experience with event-time processing, watermarks, and windowing.
• Strong Kafka expertise including producers, consumers, partitioning and offset management.
• Solid Java development skills with concurrency and memory management.

Responsibilities

• Design and develop real-time stream processing applications using Apache Flink and Java.
• Implement stateful processing with keyed/operator state and savepoints.
• Apply event-time semantics and windowing for accurate streaming results.
• Tune performance: parallelism, operator chaining and backpressure handling.
• Integrate with Kafka for ingestion and delivery pipelines.
• Ensure data consistency and fault tolerance in cloud-native deployments.

Skills

Flink with Java

Kafka

State management (operator/keyed)

Event-time processing

Java performance tuning

Concurrency & memory management

Tools

RocksDB backend

Kryo/Avro/Protobuf serialization

Job description

Experience: 3-8 years
Location: TVM / COK / CHENNAI / BLR

Overview

We are looking for a highly skilled Flink Java Developer with 3–8 years of experience in building real‑time streaming applications at scale. The ideal candidate will have strong hands‑on expertise in Apache Flink (Java), solid working experience with Kafka, and knowledge of streaming data design patterns. Familiarity with Flink PaaS solutions (e.g., Decodable, Confluent Cloud, Kinesis Data Analytics) is a strong plus.

Key Responsibilities

• Design and develop real‑time stream processing applications using Apache Flink and Java.
• Implement stateful stream processing (keyed state, operator state, checkpointing, savepoints).
• Apply event‑time semantics, watermarking, and windowing for accurate streaming computations.
• Optimize Flink job performance (parallelism, operator chaining, backpressure handling, checkpointing strategy).
• Integrate with Kafka (mandatory) for ingestion and delivery pipelines.
• Tune serialization/deserialization (Kryo, Avro, Protobuf, POJO) for high throughput and efficiency.
• Implement Async I/O patterns in Flink to integrate with external systems (e.g., MongoDB/NoSQL).
• Connect pipelines to NoSQL databases (MongoDB preferred) for persistence and lookups.
• Deploy and monitor applications in cloud‑native environments; exposure to Flink PaaS solutions is advantageous.
• Ensure high availability, fault tolerance, and data consistency across distributed systems.

Required Skills & Experience

• 3–8 years of hands‑on Apache Flink experience with Java.
• Strong expertise in Kafka (producer, consumer, partitioning, offset management).
• Knowledge of Flink state management (operator/keyed state, RocksDB backend).
• Experience with event‑time processing, watermarks, windowing, and broadcast state.
• Solid Java development skills including concurrency, performance tuning, and memory management.

Good to Have

• Experience with Flink PaaS solutions (Decodable, Confluent Cloud, Kinesis Analytics, etc.).
• Serialization tuning with Kryo, Avro, Protobuf, or POJO optimization.
• Familiarity with Async Flink operators (async lookups, async I/O).
• Experience with NoSQL databases such as MongoDB.
• Exposure to Flink metrics, job monitoring, and performance optimization.

Desired Qualities

• Strong problem‑solving and debugging skills.
• Effective communication and collaboration with cross‑functional teams.
• Proactive, ownership‑driven approach to handling large‑scale, critical data pipelines.
• Ability to adapt quickly in fast‑paced, cloud‑first environments.