Data Platform Engineer

DAZN; Hyderabad; On-site; INR 800,000 - 1,200,000; Full time

Job summary

DAZN in Hyderabad is looking for a Data Platform Engineer to design and build scalable data pipelines. This role involves working with cutting-edge technologies like Python, Apache Airflow, and various AWS services to support data processing.

The Data Platform Engineer will be responsible for developing data processing frameworks, monitoring performance, and implementing CI/CD pipelines. Join DAZN and reshape digital sports broadcasting for millions of fans worldwide.

Qualifications

• Proven experience in designing and building data pipelines.
• Strong knowledge of AWS services for data processing.
• Experience in developing reusable data processing frameworks.

Responsibilities

• Design, build, and maintain scalable data pipelines.
• Develop Python-based data processing frameworks.
• Monitor pipeline performance and troubleshoot failures.
• Build CI/CD pipelines for data engineering.

Skills

Python

Apache Airflow

AWS Services (Glue, Firehose, S3, Batch, Lambda, ECS, EKS)

Spark

Kafka

Job description

Data Platform Engineer

Department: 61-416 - Technology - Hyderabad

Employment Type: Permanent - Full Time

Location: India - Hyderabad

Reporting To: Madhu Babu Tanikella

Description

DAZN is the world’s leading sports streaming platform, reshaping the way fans experience live and on-demand sports. With cutting‑edge technology and a global footprint, DAZN is building the future of digital sports broadcasting. Our Hyderabad Tech Hub plays a pivotal role in delivering scalable, high‑performance solutions that power millions of users worldwide.

Key Responsibilities

• Design, build, and maintain scalable and reliable data pipelines using Python, Apache Airflow, AWS Services like Glue/Firehose/S3/AWS Batch/Lambda/ECS/EKS to support batch and near real‑time processing.
• Develop reusable, modular, and efficient Python-based/Spark/Kafka/ data processing frameworks and utilities.
• Monitor pipeline performance, troubleshoot failures, and implement automated alerting and recovery mechanisms.
• Build CI/CD pipelines for automated deployment of data engineering pipelines.