Lead Analytics Engineer, IN at DAZN
Job Description
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.
The Role:
Join DAZN’s Data Engineering team as a Lead Analytics Engineer,IN and help shape the future of sports streaming through data. You’ll lead the design, development, and optimization of scalable data pipelines and platforms that power insights across our global operations. Working with cutting-edge technologies and diverse data sources — from streaming analytics to fan engagement — you’ll play a key role in enabling data-driven decisions that enhance the experience for millions of sports fans worldwide.
- Design, build, and maintain scalable data pipelines and ETL processes across cloud platforms.
- Lead the architecture and implementation of DAZN’s data infrastructure to support analytics, ML, and reporting.
- Collaborate with data scientists, analysts, and product teams to deliver high-quality, reliable datasets.
- Optimize data storage, processing, and performance for large-scale, real-time data streams.
- Ensure data quality, governance, and security across all data environments.
- Mentor and guide a team of data engineers, fostering best practices and technical excellence.
- Evaluate and adopt new data technologies to continuously improve DAZN’s data ecosystem.
- Strong experience with Python, SQL, and modern data engineering frameworks.
- Expertise in building and optimizing ETL/ELT pipelines and data workflows.
- Hands-on experience with cloud data platforms (e.g., AWS, GCP, or Azure).
- Proficiency in big data technologies like Spark, Databricks, or Kafka.
- Solid understanding of data modeling, data warehousing, and distributed systems.
- Experience with orchestration tools such as Airflow, dbt, or similar.
- Knowledge of data governance, security, and best practices for scalable data systems.
- Familiarity with CI/CD, infrastructure-as-code, and DevOps concepts.
- Excellent problem-solving, leadership, and collaboration skills.