AI and Data Engineer – Finance Enterprise Data Solutions

The ideal candidate should possess:

• Bachelor's or Master's degree in Data Science, Computer Science, Information Systems, Engineering, Analytics, or a related quantitative discipline.
• 3 to 6 years of proven experience in data engineering, analytics, and data solution delivery within large-scale enterprise environments.
• Strong proficiency in SQL and Python, with the ability to design, develop, optimize, and support scalable data pipelines and analytical solutions.
• Hands-on experience with modern cloud-based data platforms and services, including Azure, Azure Data Factory (ADF), Databricks, Snowflake, BigQuery, and related data ecosystem technologies.
• Solid understanding of data architecture principles, including data warehousing, data lakes, lakehouse architectures, data modeling, ETL/ELT frameworks, and data integration best practices.
• Experience designing, building, and maintaining scalable, reliable, and secure data products that support business intelligence, advanced analytics, and AI-driven solutions.
• Strong understanding of Artificial Intelligence (AI), Generative AI, and AI-assisted productivity tools, with the ability to apply AI responsibly, securely, and ethically in accordance with enterprise governance standards.
• Demonstrated ability to leverage AI technologies to improve productivity, automate repetitive processes, enhance data-driven decision making, and accelerate solution development and delivery.
• Experience developing dashboards, reports, and analytical solutions using enterprise BI platforms such as Power BI, Sigma Reporting, SAP BusinessObjects (BOBJ), Web Intelligence (WebI), or equivalent reporting tools.
• Knowledge of SAP enterprise data platforms, including SAP ECC, SAP BW, SAP S/4HANA, and SAP HANA, is highly desirable.
• Exposure to Machine Learning Operations (MLOps), AIOps, data observability, model lifecycle management, or AI solution deployment practices is an added advantage.
• Strong business and data domain acumen, particularly in Finance, Accounting, Treasury, Supply Chain, or related enterprise functions, is preferred.
• Experience collaborating within Agile teams and applying Agile delivery methodologies, including sprint planning, backlog management, daily stand-ups, reviews, and retrospectives.
• Excellent analytical, problem-solving, communication, and stakeholder management skills, with the ability to translate business requirements into scalable data and AI solutions.

Preferred Personal Traits:

• Analytical and Detail-Oriented: Excellent problem-solving skills with a keen eye for accuracy and data integrity.
• Collaborative Communicator: Strong ability to work cross-functionally, bridging gaps between technical and business teams through clear communication.
• Data-Driven Mindset: Passionate about transforming data into actionable insights to support strategic decisions.
• Resilient and Adaptable: Thrives in fast-paced, high-pressure environments, adept at multitasking and prioritizing effectively.

This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. Job posting details (such as work model, location or time type) are subject to change.

ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.