Data Engineer

SUMMARY:
Our client in the banking sector seeks to employ a Data Engineer yo assemble large, complex data sets to meet functional/non-functional requirements, adhering to best big data practices.

POSITION INFO:
Experience: Minimum of 5 years of experience, preferably in a financial background as a Data Engineer.
Education: Bachelor’s degree in Information Technology, Computer Science, Software Development, Engineering , or a related field.
Job Description:

Key Accountabilities:

• Source data from internal and external sources, engaging with technical subject matter experts.
• Explore, analyze, and profile data from various internal and external sources, assisting data scientists in preparing data for analytical purposes.
• Ensure delivered solutions meet Systems Integration and User Acceptance Testing criteria.
• Productionalize solutions and ensure daily data refresh processes run successfully.

• Understand the technical landscape and bank-wide architecture connected to or dependent on the supported business area.
• Translate data architecture direction and associated business requirements, leveraging analytical and creative problem-solving skills to synthesize data solution designs.
• Participate in design thinking processes to deliver data solution blueprints.
• Utilize state-of-the-art relational and No-SQL databases, integration, and streaming platforms to deliver sustainable business-specific data solutions.
• Design data retrieval, storage, and distribution solutions, contributing to all phases of the development lifecycle.
• Develop high-quality data processing, retrieval, storage, and distribution designs in a test-driven and domain-driven/cross-domain environment.
• Build analytics tools utilizing the data pipeline, producing well-organized, optimized, and documented source code and algorithms.
• Create and maintain sophisticated CI/CD pipelines, supporting deployment to multi-site environments.
• Automate tasks through appropriate tools and scripting technologies (e.g., Ansible, Chef).
• Debug existing source code and polish feature sets.
• Assemble large, complex data sets meeting business requirements and manage the data pipeline.
• Build infrastructure to automate extremely high volumes of data delivery.
• Create data tools for analytics and data science teams, optimizing data sets for business benefit.
• Ensure designs and solutions align with technical organization principles (self-service, repeatability, testability, scalability, and resilience).
• Apply general design patterns and paradigms to deliver technical solutions.
• Support the continuous optimization, improvement, and automation of data processing, retrieval, storage, and distribution processes.
• Ensure quality assurance and testing of all data solutions align with QA Engineering and architectural guidelines.
• Implement and align with Group Security standards to ensure the undisputable separation, security, and quality of the organization's data.
• Contribute to and ensure solutions align with the design and direction of Group Architecture, adhering to data standards, principles, preferences, and practices.
• Contribute to and ensure solutions align with the design and direction of Group Infrastructure standards and practices (e.g., OLA’s, IAAS, PAAS, SAAS, Containerization).
• Monitor the performance of data solution designs and ensure ongoing optimization of data solutions.
• Stay updated on data processing, retrieval, storage, and distribution technologies and processes (global best practices and trends) to ensure best practices.

• Coach and mentor other engineers.
• Conduct peer reviews, testing, and problem-solving within and across the broader team.
• Build data science team capability in the use of data solutions.

• Identify technical risks and mitigate these (pre, during & post deployment).
• Update/Design all application documentation aligned to organizational technical standards and risk/governance frameworks.
• Create business cases and solution specifications for various governance processes (e.g., CTO approvals).
• Participate in incident management and DR activity, applying critical thinking, problem-solving, and technical expertise to resolve major incidents.
• Deliver projects on time and within budget.