Experience Core competencies, knowledge, and experience]:

• Good knowledge on Database & data warehouse design
• Good analytical skills. Comprehensive written skills
• Good Knowledge on AI/ML techniques, CI/CD, MLOPS, data pipelines tools and cloud technologies. 
• Multicultural exposure. Working with virtual teams. Leadership & Inter-functional relationships
• Autonomous, agile, flexible and results oriented. Capable of delivering under challenging situations. Strong focus on delivery.
 

Influencing skills. Must have technical / professional qualifications:

• Engineering degree on Telecoms, IT or equivalent 
• A minimum of 5 experience in these topics: 
o In-depth understanding of database structure principles. Proficiency in SQL & NO-SQL
o Proficiency in MS Excel 
o Familiarity with various database management systems like MySQL, Oracle, and SQL Server. 
o Ability to create conceptual, logical, and physical data models. 
o Knowledge of data modelling tools like Erwin, IBM Data Architect, and others. 
o Designing and implementing ETL processes and workflows. 
o Knowledge of ETL tools like Talend, Apache Nifi, or Microsoft SSIS. 
o Working knowledge of big data technologies like Hadoop, Spark, and others. 
o Experience with data storage solutions like HBase, Cassandra, and MongoDB. 
o Understanding of data warehouse concepts, structures, and best practices. 
o Implementing and maintaining data warehousing solutions. 
o Experience in gathering and analysing system requirements. 
o Knowledge of data mining and segmentation techniques 
o Familiarity with data visualization tools (e.g., Tableau, D3.js and R) 
o Familiarity with cloud platforms and services like AWS, Azure, or Google Cloud. 
o Ability to design and deploy data solutions in a cloud environment. 
o Ensuring data security, privacy, and compliance with relevant regulations. 
o Implementing data encryption, masking, and auditing techniques. 
o Ability to analyze data to derive insights and support business decision-making. 
o Proficiency in using data analysis tools and languages like Python, R, or SAS. 
o Should be able to comprehend the company’s goals and translate them into data architecture and management strategies. 
o Should have proven leadership skills to mentor the technical team and promote quality standards and the right vision of the product. 
o Ability to develop and implement strategic plans related to data acquisition, storage, and usage to support business objectives. 
o Identifying and mitigating risks related to data management and security. 
o Should be able to prioritize tasks and organize the team for efficient work. 
o Should participate in meetings with customers, collaborate with internal and external teams and have discussion with upper-level management 
o Ensure that data architecture and practices comply with industry standards. 
 

Nice to have :

• Knowledge of Telecom domain standards & protocols
• Experience in Data Engineering products & technologies

• Knowledge of Machine Learning and AI techniques Responsibilities Key accountabilities and decision ownership: 
• Communicate with Engineering and Operations stakeholders in early stages of a request, to drive the alignment between user requirements and functional & non-functional requirements. Ensure true business needs are clearly identified and clearly understood at the root so that the most effective and efficient solutions can be derived. 
• Manage relationship with business, manage key stakeholders’ expectations. 
• Look for synergies and innovation across Europe to serve the local markets. 
• Enhance & evolve the continuous monitoring and continuous management framework deployed within European markets and GCP. 
• Elaborate planning for the systems according to network evolution, user requirements and life cycle. 
• Manage and execute the detailed budget. Contribute for the long-range planning. Ensure the timely delivery, meeting, or exceeding Capex targets. 
• Escalate critical issues to sp

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