About Marriott:
Marriott Tech Accelerator is part of Marriott International, a global leader in hospitality. Marriott International, Inc. is a leading American multinational company that operates a vast array of lodging brands, including hotels and residential properties. It consists of over 30 well-known brands and nearly 8,900 properties situated in 141 countries and territories.
Role Title: Reporting and Analytics Senior Engineer II – Procurement Technology
Position Summary:
Reporting and Analytics Senior Engineer II will be a highly engaged and motivated senior engineer who will be responsible for designing, building and maintaining reporting and analytics systems and dashboards. This role will design and develop integration solutions to multiple data sources leveraging expertise in data modelling, SQL, Python, cloud data warehousing, ETL processes, and BI tools. The ideal candidate should have a blend of technical and analytical skills to manage and interpret financial data
We are transforming the procurement business by enabling best-in-class procurement technology at Marriott. With leaders who have driven this transformation elsewhere, we need engineers who are excited about evolving the organization and setting the gold standard. We are early in this journey and thought leadership, with the ability to bring others along, is key.
Job Responsibilities:
- Design, build and maintain reports and dashboards to visualize procurement data within the procurement source-to-pay platform or external BI tools (like Tableau or Power BI).
- Develop tailored reports and interactive dashboards using the built-in reporting features in the procurement source-to-pay platform
- Design and optimize data models and data structures
- Define and design data flow, data extraction, data cleaning and extraction solutions
- Collaborate with business stakeholders to understand reporting needs and to define key performance indicators (KPIs)
- Serve as a subject matter expert on built-in analytics features in the procurement source-to-pay platform, including out-of-box reports, customizable dashboards, and the ability to drill down into operational data.
- Serve as the lead data and analytics engineer for procurement technology
- Collaborate with technical and business teams to analyze procurement processes, identify areas for improvement, and recommend changes to enhance efficiency and effectiveness within the procurement platform
- Analyze data to identify trends, patterns, and anomalies related to procurement activities, such as spend by category, supplier performance, cost savings, and contract compliance.
- Support the procurement business to make data-driven decisions within their procurement operations, driving efficiency, cost savings and strategic sourcing
- Experience in a data or analytics engineering role, with a focus on building and maintaining reporting and analytics systems and dashboards.
- Maintain industry knowledge and enhance subject matter expertise, identify trends and changes in technology and automation strategies.
- Assist with interviewing talent, provide peer reviews/feedback frequently and foster a modern engineering culture.
- Serve in the on call rotation
Managing Priorities and Delivery:
- Develop specific goals and plans to prioritize, organize, and accomplish work
- Provide technical leadership for successful platform and project implementations
- Assist with determining priorities, schedules, plans and necessary resources to complete projects on schedule
- Assist with reviewing vendor proposals and selecting appropriate vendor for services/technologies
- Understand and meet the needs of key stakeholders
- Communicate concepts in a clear and persuasive manner that is easy to understand
- Demonstrate an understanding of business priorities
- Support achievement of performance goals, budget goals, team goals, etc.
- Perform other reasonable duties as required for this position
Skill and Experience:
- Experience in a data or analytics engineering role, with a focus on building and maintaining reporting and analytics systems and dashboards.
- Strong technical skills in data manipulation, analysis, and visualization, along with experience in building and managing data pipelines and reporting systems.
- Strong communication and leadership skills to collaborate with stakeholders and guide less experienced team members. Key areas of expertise include SQL, Python, cloud data warehousing, ETL processes, and BI tools.
- Blend of technical and analytical skills to manage and interpret financial data.
- Key skills include strong SQL proficiency, experience with data modeling and warehousing, and knowledge of ETL / ELT processes.
- Familiarity with cloud platforms (AWS, Azure, GCP) and tools like dbt is also crucial. Furthermore, strong communication and problem-solving abilities are essential for collaborating with stakeholders and translating business needs into actionable insights.
Data Classification and Harmonization:
- Utilizing AI-driven data classification to cleanse and harmonize datasets is a key task.
Communication and Collaboration:
- The ability to communicate technical concepts to both technical and non-technical stakeholders is important.
Data Manipulation and Analysis:
- Proficiency in SQL for querying and manipulating large datasets, and Python for data analysis, scripting, and automation.
Cloud Data Warehousing:
- Experience with cloud platforms like AWS, Azure, or Google Cloud and their respective data warehousing solutions.
ETL Processes:
- Experience with extract, transform, load processes and tools to build data pipelines. Familiarity with frameworks like Airflow is also beneficial.
BI Tools:
Experience with Business Intelligence tools like Tableau, Looker, Power BI, or others, for creating visualizations and dashboards.
Data Modeling:
- Understanding of dimensional modeling, fact tables, and dimension tables, and experience with tools like dbt (data build tool).
Data Quality and Testing:
- Experience implementing data quality checks and processes to ensure accuracy and reliability.
Big Data:
- Experience with big data technologies like Spark, Presto, or Hadoop is a plus.
AI/ML Expertise:
- Experience with Large Language Models (LLMs) and related techniques like prompt engineering and fine-tuning.
- Solid understanding of various machine learning paradigms and practical experience deploying them.
- Knowledge of reasoning frameworks, agent architectures, and Retrieval-Augmented Generation (RAG).
Education and Certifications:
- Undergraduate degree in an engineering or computer science discipline and/or equivalent experience / certification.
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Marriott’s core values:
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