Senior Flink Data Engineer
IN318 - Hyderabad Sattva Knowledge Park - Hi-Tech City (IN318), India
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DXC Technology
DXC Technology helps global companies run their mission-critical systems and operations while modernizing IT, optimizing data architectures, and ensuring security and scalability across public, private and hybrid clouds.Job Description:
Senior Developer (Apache Flink, Kafka)
Job Location: Hyderabad / Bangalore / Chennai / Kolkata / Noida/ Gurgaon / Pune / Indore / Mumbai
Job Details
• Overall 8+ years of experience in data processing.
• 2 to 3 years of experience in Apache Flink & Kafka experience along with Microsoft Azure Cloud
• Write and optimize Flink jobs, which are applications that process data streams. This includes using Flink's APIs (e.g., DataStream API, Table API) to create complex data processing workflows.
• Fine-tune Flink applications for performance, ensuring they handle high throughput and low latency. This involves adjusting parameters, optimizing resource usage, and addressing performance bottlenecks.
• Design and build data pipelines to process batch and analyze streaming data in real time. This involves setting up data ingestion, transformation and output processes.
• The candidate will provide practical experience in java as a full stack developer experience in providing technical leadership.
• Data analytics experience using SQL
• Preferred knowledge in Mongo DB / Kubernatives / Graph QL
• The candidate will provide practical experience on the Azure cloud platform in development and deployment with data migration projects.
At DXC Technology, we believe strong connections and community are key to our success. Our work model prioritizes in-person collaboration while offering flexibility to support wellbeing, productivity, individual work styles, and life circumstances. We’re committed to fostering an inclusive environment where everyone can thrive.
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: APIs Azure Data Analytics Data pipelines Flink Java Kafka Pipelines SQL Streaming
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