Data Engineer

Required Education
• A 4-year degree and/or Master’s degree from an accredited college or university, or equivalent experience.

Technical Skills (Must-Have)
• 5–7 years’ experience in data management, data engineering, or data operations (data design, data quality, metadata, governance, etc.)
• Experience with development and delivery of microservices using serverless AWS services (S3, RDS, Aurora, DynamoDB, Lambda, SNS, SQS, Kinesis, IAM)
• 4+ years of experience in a cloud environment (AWS, Snowflake)
• Strong SQL and Python

Soft Skills (Must-Have)
• Verbal and written communication skills with ability to clearly communicate complex technical ideas
• Problem solving skills, customer service, and interpersonal skills
• Ability to work collaboratively in a complex, rapidly changing, and culturally diverse environment

Desired Skills (Nice to Have)
• Strong AWS experience, including SageMaker, S3, RDS, CloudWatch and related services
• Strong Snowflake experience
• Strong SQL and Python development skillset
• Understanding of logical data domains, primarily Customer & Equipment Domains
• Experience in Data Operations, Tier 2 Support, or comparable Data Engineering Support role
• Strong knowledge of end-to-end data lifecycle across traditional data warehouses, relational databases, operational data stores, business intelligence reporting, and big data analytics
• Knowledge of data technology products and components for Big Data and Cloud (AWS, Data Lakes, and similar)

Job Responsibilities
• Perform all necessary data related tasks including data design, data quality, data triage, data governance, or data architecture – SQL, Snowflake, AWS
• Develop break/fix solutions and address root causes in data pipeline implementation/code – Python, AWS
• Develop scripts and automation tools to better detect and correct data issues
• Develop monitoring and alerting capabilities to proactively detect data issues
• Work directly on complex application/technical problem identification and resolution, including responding to off-shift and weekend support calls
• Identify, investigate, and obtain resolution commitments for platform and data issues to maintain and improve quality and performance of assigned digital product data
• Issue Identification: Review reports from customers, dealers, industry representatives, and subsidiaries
• Issue Investigation: Perform statistical analysis, data triage, and infrastructure problem-solving
• Issue Resolution: Identify root causes, create SageMaker scripts to fix data, and perform break/fix tasks on data pipeline code
• Communicate with end users and internal customers to help direct development, debugging, and testing of application software for accuracy, integrity, interoperability, and completeness
• Participate in technical sync-ups and meetings with internal team including US and offshore teams
• Liaise with designers, engineers, and support teams to improve data pipeline performance and reliability
• Perform other job duties as assigned by Caterpillar management from time to time