Data Engineer

2 weeks ago

Bengaluru, India Jio Full time

Role : Data Engineer Location : Gurgaon/Bangalore/Mumbai Years of Experience : 5-12 Years Must Have: SQL, Spark, Spark sql, spark streaming, Scala/Python, Azure/AWS, Kafka Good to Have : NoSQL (Mongo/Cassandra), Neo4J, Prometheus, Flink, Iceberg Company Overview Jio stands at the forefront of India's telecom industry, boasting over 400 million customers. Beyond telecom, Jio powers a vast array of digital apps and services, offering solutions for both B2C and B2B markets. With cutting-edge technology, including 5G solutions, AI/ML platforms, cloud-native systems, and BSS solutions, Jio revolutionizes media and telecommunications. Headquartered in Navi Mumbai, Maharashtra, Jio operates with more than 10001 employees across India. For more information, visit Jio Platforms . Job Overview Jio is seeking a skilled Data Engineer for a Mid-Level position, based in Bangalore, Mumbai, or Gurgaon. This full-time role involves designing, building, and maintaining scalable data pipelines and systems. The ideal candidate will have a strong background in data technologies and platforms, contributing to advanced data solutions and AI-driven insights across Jios telecom and digital service frameworks. Qualifications and Skills Proficiency in SQL (Mandatory skill): Essential for querying, manipulating, and analyzing data within relational databases. Experience with spark streaming (Mandatory skill): Crucial for processing real-time data streams efficiently within big data solutions. Understanding of NoSQL databases (Mandatory skill): Vital for handling unstructured or semi-structured data formats in data-intensive applications. Experience in Spark: Key for large-scale data processing and analytical tasks within Jio's extensive data ecosystem. Proficiency in Spark SQL: Important for leveraging Spark's SQL interface to perform complex analytical queries effectively. Familiarity with Azure: Necessary for managing data solutions and storage within Microsofts cloud environment. Understanding of AWS: Essential for leveraging Amazons cloud services for scalable data storage and processing solutions. Experience with Kafka: Important for building real-time data pipelines and streaming applications. Roles and Responsibilities Design, develop, and maintain robust data pipelines for efficient data transformation and integration across platforms. Collaborate with cross-functional teams to gather and analyze data requirements, ensuring alignment with business goals. Implement real-time data streaming solutions using spark streaming, achieving high throughput and low latency data processing. Utilize SQL and NoSQL databases to manage, store, and retrieve large volumes of structured and unstructured data effectively. Optimize data workflows, improving performance and scalability of data-driven applications and reporting solutions. Ensure the security and integrity of data, implementing best practices for data protection and compliance. Participate in the deployment and monitoring of AI-driven analytics platforms, enhancing data-driven decision-making processes. Stay updated with emerging data technologies, recommending innovative solutions to foster continuous improvement.

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