Requirements

Expected technologies

SQL

Python

Java

AWS

Our requirements

• Strong experience with database technologies (SQL, NoSQL), data warehousing solutions, and big data technologies (Hadoop, Spark).
• Proficiency in programming languages such as Python, Java, or Scala.
• Experience with cloud platforms (AWS, Azure, Google Cloud) and their data services. Certifications in cloud platforms (AWS Certified Data Analytics, Google Professional Data Engineer, etc.) as a plus.
• Deep understanding of ETL processes and data pipeline orchestration tools (Airflow, Apache NiFi).
• Knowledge of data modelling, data warehousing concepts, and data integration techniques.
• Strong problem-solving skills and ability to work under pressure and excellent communication and interpersonal skills.
• Experience in the banking or financial services industry and familiarity with regulatory requirements related to data security and privacy in the banking sector.
• Experience with machine learning and data science frameworks.

Your responsibilities

• Leadership and Team Management: Lead, mentor, and develop a team of data engineers, establish best practices for data engineering and ensure team adherence, coordinate with other IT teams, business units, and stakeholders.
• Data Pipelines Integration and Management.
• Design and implement scalable data architectures to support the bank's data needs.
• Develop and maintain ETL (Extract, Transform, Load) processes.
• Oversee the integration of diverse data sources into a cohesive data platform.
• Ensure data quality, data governance, and compliance with regulatory requirements, ensure the data infrastructure is reliable, scalable, and secure, develop and enforce data security policies and procedures.
• Monitor and optimize data pipeline performance.
• Troubleshoot and resolve data-related issues promptly.
• Implement monitoring and alerting systems for data processes.