16 PhonePe Jobs

Responsibilities:

Design, develop, test, and maintain highly scalable and performant data infrastructure (Analytics Architecture).
Build and optimize complex, high-performance integrated ETL/ELT pipelines for a unified customer view (Integrated Customer View).
Establish and enforce standardized metadata management, access protocols, and data discovery mechanisms (Information Layer).
Implement robust data quality checks and monitoring systems across the data lifecycle (Instrumentation layer).
Evaluate, prototype, and integrate cutting-edge big data technologies and software engineering tools into existing and new infrastructures.
Proactively identify and research opportunities for novel data acquisition and innovative uses of existing data.
Lead collaboration efforts with Data and IT teams to enhance the data platforms capabilities and reliability.
Develop and implement comprehensive data collection, storage, and retrieval monitoring processes.
Drive collaboration with Engineering teams to establish and maintain data standards and best practices.
Develop a deep understanding of the business and its various domains, translating business requirements into technical data solutions.
Actively contribute to the open-source community and share knowledge with the team.
Effectively lead and mentor junior team members, fostering a collaborative and high-performing environment.

Requirements:
Extensive hands-on experience with programming languages: Python, Java, Scala.
Deep expertise in big data stacks, including:
Distributed systems: Spark (PySpark), Hadoop, Presto, Hive.
Message Queueing systems: Kafka, RabbitMQ, NSQ.
Databases (Relational NoSQL): PostgreSQL, MySQL, MongoDB.
Proven experience gathering and analyzing complex system requirements.
In-depth understanding of advanced database structure principles, data warehousing methodologies, data mining concepts, and segmentation techniques.
Significant experience with cloud computing platforms (AWS, GCP) and UNIX environments.
Extensive experience with AWS services such as EMR, Lambda, Step Functions, S3, and Redshift.
Experience architecting, implementing, and monitoring large-scale big data analytics solutions.
Strong analytical and problem-solving skills with a natural curiosity about big data and emerging technologies.
Strong DevOps/DataOps skills and experience with CI/CD pipelines for data infrastructure.
Background: Bachelors or Masters degree in Computer Science (preferred) or a related field.