About this role
Why Join DAZN? Joining DAZN in Hyderabad means being part of a cutting-edge sports streaming company in a vibrant tech hub. You’ll work alongside passionate, talented professionals on innovative projects that reach millions of fans worldwide. Hyderabad offers a dynamic work environment with a great balance of career growth and lifestyle. If you’re excited about shaping the future of live and on-demand sports entertainment, DAZN Hyderabad is the perfect place to make your mark and grow your career. Role Overview: DAZN is seeking a highly motivated Analytics Engineer to join our Data & Analytics team. This role bridges the gap between Data Engineering and Analytics, enabling trusted, scalable, and business-ready data products that support decision-making across product, marketing, commercial, finance, and customer experience functions. The ideal candidate will have strong expertise in dbt, SQL, and Python, with experience building modern data models, transforming large-scale datasets, and delivering reliable analytics solutions in a cloud data platform environment. Design, develop, and maintain scalable data models using dbt following best practices such as modularity, testing, documentation, and version control. Write complex and optimized SQL transformations to create curated datasets and business metrics. Develop and maintain Python scripts and frameworks for data processing, automation, quality validation, and analytics workflows. Collaborate with Data Engineers to ingest, transform, and manage data from multiple internal and external sources. Build and maintain dimensional models, fact tables, and semantic layers that support reporting and self-service analytics. Implement data quality checks, monitoring, and testing using dbt tests and custom validation frameworks. Work closely with Product, Marketing, Finance, and Operations stakeholders to understand business requirements and translate them into scalable data solutions. Optimize data pipelines and transformation processes for performance, reliability, and cost efficiency. Create and maintain technical documentation, data lineage, and metadata standards. Support BI and reporting tools by delivering clean, governed, and trusted datasets.