Lead Data Engineer: Cloud Pipelines & Real-Time Data (AWS)

Caterpillar Financial Services Corporation

Irving (TX)

On-site

USD 128,000 - 209,000

Full time

3 days ago
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Benefits offered by this job

Health benefits
401(k) plan
Paid time off
Tuition reimbursement
Bonus
Career development

Job summary

Caterpillar Inc. in Irving, TX is seeking a Lead Data Engineer to design, build, and maintain scalable data pipelines, microservices, and cloud data platforms delivering high-quality data for multiple teams.

You will drive architecture, performance, reliability, and continuous improvement in a fast-paced, Agile environment. Responsibilities include leading design of data pipelines, orchestrating real-time and batch processing, and ensuring data integrity across distributed ecosystems while

Qualifications

  • Bachelor's degree in a related field and 8+ years of data engineering experience.
  • Strong experience with Python, Java, SQL and cloud data platforms.
  • Proven ability to lead teams and deliver scalable data solutions.

Responsibilities

  • Design, build, and maintain scalable data pipelines and microservices.
  • Lead cloud-based data platforms and ensure data quality and reliability.
  • Collaborate with stakeholders to translate requirements into scalable architectures.
  • Implement testing, monitoring, and automation for data systems.

Skills

Python
Java
SQL
AWS data services
CI/CD
Data pipelines

Education

Bachelor’s degree in Computer Science, Computer Engineering, or related field

Tools

Kinesis
S3
DynamoDB
EventBridge
Azure DevOps
Jira
Jenkins

Job description

Caterpillar Inc. in Irving, TX is seeking a Lead Data Engineer to design, build, and maintain scalable data pipelines, microservices, and cloud data platforms delivering high-quality data for multiple teams.

You will drive architecture, performance, reliability, and continuous improvement in a fast-paced, Agile environment. Responsibilities include leading design of data pipelines, orchestrating real-time and batch processing, and ensuring data integrity across distributed ecosystems while

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