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At Vodafone, we’re not just shaping the future of connectivity for our customers – we’re shaping the future for everyone who joins our team. When you work with us, you’re part of a global mission to connect people, solve complex challenges, and create a sustainable and more inclusive world. If you want to grow your career whilst finding the perfect balance between work and life, Vodafone offers the opportunities to help you belong and make a real impact.
Job Responsibility:
Delivering end to end development solutions for BI and Big Data quality tasks, including pipelines, data trends and dashboards
Managing the system optimization, monitoring workflow performance, administering DWH applications and Big Data clusters
Managing vendor communications and handling system upgrades
Design, develop, and implement solutions to monitor, validate, and improve data accuracy, consistency, and completeness
Build data quality gates to ensure and maintain scalable data pipelines for processing and validating large datasets efficiently
Develop and enhance ETL processes to ensure seamless data movement across systems while maintaining data quality dashboards
Ensure adherence to data governance policies, regulatory standards, and best practices for data management
Investigate data anomalies, identify root causes, and implement corrective measures proactively
Optimize query performance, database indexing, and system configurations to enhance efficiency
Work closely with data analysts, engineers, business teams, and vendors to ensure data quality objectives are met
Develop automation scripts and monitoring frameworks to streamline data quality checks and alert on anomalies
Requirements:
Bachelor of computer Science or related domains
0 to 1 years in engineering, specifically in building quality gates for data pipelines, ensuring data accuracy, and administering distributed systems
Experience in bigdata systems and technologies such as Java, Python, NoSQL, Node.js, Angular, Kafka, Yarn, Hbase, Zookeeper
Understanding of distributed systems like Hadoop (HDFS)
Knowledge of data processing frameworks, such as Apache Hadoop (MapReduce), Apache Spark, Apache Kafka
Understanding of data warehousing concepts and technologies
Familiarity with ETL tools and processes for efficiently moving and transforming data