Technical Product Manager: Data Pipelines & AI Enablement

Caterpillar Financial Services Corporation; Irving (TX); On-site; USD 128,000 - 209,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

Paid time off

401(k) plan

Health Savings Account (HSA)

Flexible Spending Accounts (FSAs)

Career development

Incentive bonus

Disability insurance

Life insurance

Parental leave

Tuition reimbursement

Relocation assistance

Job summary

Caterpillar Inc. is seeking a Technical Product Manager for Data Collection & Pipeline to define strategy, roadmap, and delivery of data products enabling AI, ML, analytics, and autonomous systems.

You will own the end-to-end data ecosystem, collaborating with analytics, data science, and engineering teams to drive data quality, pipelines, labeling, and governance across multiple squads while focusing on customer value and scalable platforms.

Qualifications

• Knowledge of business analysis techniques to identify data needs and deliver scalable data products.
• Proven ability to make timely data-driven decisions balancing quality, cost, and value.
• Strong communications to align engineering, data science, and leadership teams.

Responsibilities

• Define and manage the Data Product Backlog with value-based prioritization.
• Decide on data collection capabilities, labeling workflows, and data quality standards.
• Lead data acquisition, labeling, and pipeline enhancement initiatives.
• Collaborate with engineering to deliver scalable ingestion, transformation, and storage pipelines.
• Monitor data quality metrics and governance to meet customer and business needs.

Skills

Business analysis

Decision making

Effective communications

Data product knowledge

Data collection

Data labeling

Data engineering

Pipeline development

Job description

Caterpillar Inc. is seeking a Technical Product Manager for Data Collection & Pipeline to define strategy, roadmap, and delivery of data products enabling AI, ML, analytics, and autonomous systems.

You will own the end-to-end data ecosystem, collaborating with analytics, data science, and engineering teams to drive data quality, pipelines, labeling, and governance across multiple squads while focusing on customer value and scalable platforms.