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BI Big Data Tech Lead

2 weeks ago

مصر, Egypt Vodafone Full time

**Role purpose**: to work on big data engineering pipelines, E2E solutions development, and system upgrades

**Key accountabilities and decision ownership**:

- Design scalable & reliable data ingestion solutions
- Manage day-by-day tasks in queue according to priorities set in sprint planning meetings.
- Work closely with different commercial teams to deliver personalized customer offers
- Ensure on time high quality deliverables for all data ingestion pipelines within big data platform
- Plan releases and provide proper support to released packages

**Core competencies, knowledge, and experience**:

- Passionate about Quality. A love of writing a bugs-free code, tuning and analysis through a rigorous scientific approach.
- Agile - time spent working on closely-knit teams using Agile methodologies such as Scrum and kanban
- Team Player. You enjoy collaborating with, learning from, and teaching others so we all can become better. You assume the good intent in others, and actively do your part to create a positive work environment.
- Empathy for customers - a desire to serve customers first. You love to help Vodafone’s customer to get them happy with your developed feature.

**Must have technical / professional qualifications**:

- Bachelor of computer Science or related domains
- 5+ Years Engineering Experience in building and supporting mission critical user-facing, large-scale and distributed systems.
- Open source addict - Excellent experience in open source technologies like Java, Scala, Python, C/C++, NoSQL, node.js, Angular, Must have technical / professional qualifications:

- Bachelor of computer Science or related domains
- 5+ Years Engineering Experience in building and supporting mission critical user-facing, large-scale and distributed systems.
- Open source addict - Excellent experience in open source technologies like Java, Scala, Python, C/C++, NoSQL, node.js, Angular, AWS, Kafka, Cassandra, Rabitt MQ, Zookeeper, Thrift.
- Fair understanding of private and public cloud design considerations - limitations in the areas of virtualization and global infrastructure, distributed systems, load balancing and networking, massive data storage, Hadoop, MapReduce, MemCache, Redis, Dockers/Containers and Elastic search.
- Fair Telecom knowledge
- having excellent knowledge in telecom industry and different data sources.
- Hands on experience in big data ecosystem.
- Fair knowledge in telecom industry and different data sources.
- Data integration experience is a must.