Enterprise Data Design (Data Engineer, Staff)

Qualcomm India Private Limited is seeking a Staff IT Data Engineer to join their Enterprise Architecture, Data and Services (EADS) Team. This is a pivotal role that combines advanced technical expertise with strategic data management responsibilities.

The position focuses on designing, developing, and supporting sophisticated data pipelines across multi-cloud environments, with particular emphasis on Databricks technology. The successful candidate will be responsible for managing complex data operations, from ingestion through processing to analytics provisioning, while implementing robust DevSecOps practices.

The role requires extensive experience in data engineering, with at least 5 years of specialized experience in Databricks and related technologies. Key technical requirements include mastery of Python, Java, SQL, and various ETL frameworks, along with strong expertise in cloud platforms, particularly AWS. The position demands both technical depth in data warehousing concepts and big data processing, as well as the ability to work effectively with both technical and non-technical stakeholders.

Qualcomm offers a comprehensive benefits package including world-class health coverage, financial planning support, and extensive professional development opportunities. The company's commitment to innovation and technological advancement makes this an exciting opportunity for a data engineering professional looking to work on cutting-edge projects.

The role is based in Hyderabad, India, and offers the opportunity to work with a global leader in wireless technology innovation. The position requires a combination of strong technical skills, strategic thinking, and the ability to drive data architecture decisions that will impact enterprise-wide operations.

This is an excellent opportunity for an experienced data engineer looking to take on a leadership role in a company that's at the forefront of technological innovation. The position offers significant opportunities for professional growth, exposure to cutting-edge technologies, and the chance to work on complex data challenges that have real-world impact.