DATA INTELLIGENCE ENGINEER

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Position Title: Data Innovations Engineer 

Job Summary:

The Data Innovation Engineer is responsible for designing, developing, deploying, and maintaining data innovation initiatives such as Artificial Intelligence (AI), Generative AI (GenAI), Machine Learning (ML), Advanced Analytics, and Intelligent Automation solutions for the Finance and Control Sector. The role drives innovation through the use of trusted data assets, advanced analytics, and emerging technologies to enhance accounting, financial planning, budgeting, reporting, and forecasting, enabling informed decision-making, and sustainable growth. 

Role Exposure:

• Identify, evaluate, prioritize, and implement data innovations use cases that deliver measurable outcomes.
• Design, develop, deploy, and maintain scalable data and analytics solutions leveraging trusted Enterprise Data Platform (EDP) ensuring scalability, reliability, performance, and integration with business processes and enterprise systems.
• Build and enhance data innovation capabilities within the Finance and Control Sector through reusable assets, accelerators, and best-practice solution design.
• Ensure solutions utilize governed, high-quality, and trusted data sources by applying data engineering, data quality, and data management best practices.
• Support governance, model monitoring, validation, security, and compliance controls for the responsible, ethical, and secure use of enterprise data and AI technologies.
• Drive innovation, experimentation, and continuous improvement by evaluating emerging technologies, developing proofs of concept, and scaling successful solutions into production.
• Performs other functions that may be assigned from time to time.

Qualifications:

• Bachelor’s Degree in Data Science, Computer Science, Engineering, Information Technology, Mathematics, Statistics, or related fields
• Relevant certifications in Data Engineering, Data Science, Cloud Platforms, Database Technologies, or Data Management (e.g., Microsoft Azure, AWS, Google Cloud, DAMA, Snowflake) are an advantage

• Minimum 3–5 years of experience in: Machine Learning; Artificial Intelligence; Data Science; Advanced Analytics; Data Engineering
• Experience developing end-to-end data and AI solutions in enterprise environments.

• Experience working with structured and unstructured data.
• Experience supporting Finance, Banking, Risk, or Regulatory functions is preferred.