Lead Business Intelligence Analyst

Caterpillar Inc. is a global team dedicated to creating stronger, sustainable communities through innovation and progress. The Lead Business Intelligence Analyst will contribute to the design and development of advanced data quality methods, lead programming assignments, and drive application development to deliver valuable business features.

Responsibilities:

• Contribute to the design, development, deployment, and quality of Caterpillar’s state-of-the-art digital platform by leading the development of advanced Data Quality methods and routines
• Perform programming and development assignments
• Provide programming and application/technical guidance, and assistance to other team members
• Work directly on complex application/technical problem identification and resolution, including responding to off-shift and weekend support calls
• Work independently on complex systems or infrastructure components that may be used by one or more applications or systems
• Drive application development focused around delivering valuable business features
• Maintain high standards of software quality within the team by establishing good practices and habits
• Develop a structured application/interface code, new program documentation, operations documentation and user guides in a casual, flexible environment
• Communicate with end users and internal customers to help direct development, debugging, and testing of application software for accuracy, integrity, interoperability, and completeness
• Develop new functionality and applications on cross-functional Agile project teams
• Perform integrated testing and customer acceptance testing of components that requires careful planning and execution to ensure timely, quality results

Requirements:

• This position requires a master's degree, or foreign equivalent, in Data Science, Computer Engineering, Industrial Engineering, or related field plus 4 years of experience as a Software Developer, Data Engineer, or related occupation in software development or related field
• Designing and implementing data processing and machine learning frameworks
• Python, NoSQL, and relational databases
• Compiling and standardizing diverse and non-sanitized datasets
• Integrating analytical models with existing data pipelines
• Statistical approaches, quantitative analytic methods, or data management techniques
• AWS full-stack development and services such as Athena, Glue, DynamoDB, EC2, EMR, RDS, S3, and Sage Maker
• Data warehouse systems such as: Snowflake or Hadoop
• Visualizing data using BI software such as Tableau and MS Power BI