Enterprise Data Architecture

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Our client stands out for its unique history and its dynamic future. Backed by its long-standing presence -established in 1841- strong tradition and noteworthy contribution to the economic transformation of Greece, and above all by the trust of customers, shareholders, depositors and employees alike, the Bank serves as a pillar of stability for the Greek economy, with the expertise and experience of its officers and the cutting-edge digital services it offers for your every banking need. The Group operates mainly in Greece but, also, abroad through its banking subsidiaries with a workforce of 7.889 employees as at 31 December 2023 (Greece: 6.725). End of 2023, the Bank had a total of 327 Units (313 Branches including 18 Tellerless and 14 Transaction Offices).

• Design, development, and implementation of systems, scalable applications, and data processing services with a focus on Big Data and cloud infrastructures, as well as optimization of related data flows.
• Design, implementation, and maintenance of ETL pipelines and real-time data processing.
• Selection of technology and architecture for Big Data systems and applications.
• Management of suppliers and partners in the area of Big Data and Cloud applications and systems.
• Participation and coordination of Big Data product/service development teams consisting of data engineers, project managers, and business analysts.
• Coordination and collaboration with teams to monitor the utilization of Big Data infrastructures by other technological teams within the bank, ensuring alignment with business objectives.
• Organization of production deployment and monitoring of Big Data system operations (mainly on cloud but also on-premises).
• Optimization of data storage, retrieval, and processing procedures for improved efficiency.
• Development and adoption of best practices regarding data security, governance, and compliance with regulatory frameworks.

• Internal Team Supervision: Yes – Number of team members: 5
• Project Teams Supervision: Yes – Number of project team members: 8-10 (e.g., outsourcing/flexible capacity)

• Managing large and complex modern IT projects.
• Leading technical teams and complex technical projects.
• Utilizing state-of-the-art technology and modern methodologies for application and system development.
• Access to cutting-edge technologies and development/support teams (product groups).
• Continuous learning and knowledge renewal through exposure to new technologies, tools, and methodologies.

• Degree in: Computer Science, STEM fields, Economics, Data Science.
• Postgraduate Studies:
  • Master’s degree in Software Engineering, Artificial Intelligence and Algorithms, Data Engineering, AI/ML, or People Management will be considered an asset.

• Design and development of Big Data & Cloud systems and applications.
• Team and project management in data management.
• Proven experience in Big Data & Cloud technologies.
• Significant experience in designing and optimizing large-scale distributed storage solutions and architectures.
• Experience in the financial or banking sector.
• Knowledge of data governance, security, and regulatory compliance in the banking sector.

• Strong knowledge of Big Data & Cloud technologies:
  • Programming Languages: Java, C#, Python.
  • Cloud Technologies: Microsoft Azure, Google Cloud.
  • Data Processing: Apache Beam, Spark (PySpark), Spark Streaming, MapReduce, Kafka, Hive.
  • Databases: Redis, NoSQL (CosmosDB, HBase, MongoDB, etc.), Postgres, Big Data File Formats (Parquet, Avro, Delta Lake, Iceberg, etc.). Experience with graph databases will be considered a plus.
  • Workflow Orchestration: Oozie, Azure Data Factory.
  • Visualization Tools: PowerBI.
• Strong knowledge of project management and technical project design tools.

• English: Proficiency at C1 level, certified through a relevant qualification or studies at an English-speaking university.

• Teamwork and ability to collaborate within diverse teams and projects.
• Analytical and synthetic thinking.
• Intellectual curiosity.
• Strong problem-solving skills.
• Ability to guide teams and organize the technical approach for complex Big Data projects.
• Organization, methodical approach, attention to detail, quick decision-making.
• Ability to design and strictly implement specific timelines.

• Ability to work under pressure and react quickly and calmly to emergency situations (e.g., production issues).