Data Engineering Lead

Quantum Technologies. LLC; Irving (TX); On-site; USD 84,000 - 120,000; Full time

Job summary

Quantum Technologies LLC is seeking a senior Data Engineer to lead the design and optimization of large-scale data pipelines and microservices in Python, partnering with Principal Software Engineers and Data Architects to define scalable solution architectures.

You will drive cloud-native data ingestion and streaming using AWS services (Kinesis, S3, DynamoDB, EventBridge) and ensure CI/CD delivery with Azure DevOps, Jira, and Jenkins across real-time and batch data processing.

Qualifications

• Bachelor's degree required in CS/CE or related field
• 8+ years of experience in data engineering or related disciplines
• Strong Python production experience
• Extensive AWS data services experience (Kinesis, S3, DynamoDB, EventBridge) at scale
• Experience with CI/CD tooling (Azure DevOps, Jira, Jenkins)
• Experience with data integrity, quality controls and observability

Responsibilities

• Define solution architecture with Principal Engineers and Data Architects
• Lead design and optimization of scalable data pipelines and microservices in Python
• Drive cloud-native ingestion and streaming solutions using AWS services
• Own data integration frameworks and source data pipelines for CI Autonomy initiatives
• Translate complex requirements into scalable data architectures and workflows
• Establish automated testing and data quality validation across distributed systems
• Lead monitoring, performance tuning and root-cause analysis using CloudWatch

Skills

Python

AWS

SQL

Data pipelines

Data architecture

Education

Bachelor's degree in CS/CE or related field

Tools

Azure DevOps

Jira

Jenkins

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Duration: 8 Months + Extension

Bill Rate: $74/hour (C2C)

Job Type: W-2, 1099, C2C

Client: To Be Discussed Later

Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other

Job Description

• Actively collaborate with Principal Software Engineers and Data Architects to define solution architecture
• Lead the solution design and optimization of scalable data pipelines and microservices in Python, enabling both real-time and batch data processing across enterprise platforms
• Drive the development of cloud-native data ingestion and streaming solutions leveraging AWS services including Kinesis, S3, DynamoDB, EventBridge, and related technologies
• Own the design, implementation, and operational excellence of data integration frameworks and source data pipelines supporting CI Autonomy initiatives
• Partner with business, product, and engineering stakeholders to translate complex requirements into scalable data architectures, workflows, mappings, and system designs
• Establish and enforce automated testing, data quality controls, and validation frameworks to ensure integrity, reliability, and compliance across distributed data ecosystems
• Lead operational monitoring, performance tuning, and root-cause analysis of production data platforms using observability tools such as CloudWatch to maintain high availability and service reliability
• Bachelor's degree in Computer Science, Computer Engineering, or related field
• 8+ years of experience in data engineering or related disciplines with increasing responsibility
• Extensive experience on modern, large scale, complex Caterpillar data platforms such as Helios Data Platform
• Strong foundation developing and deploying Python solutions to a production environment
• Experience leading teams to build high-throughput, scalable data pipelines
• Strong hands-on experience with AWS data services (Kinesis, S3, DynamoDB, EventBridge, etc.) at scale
• Strong in SQL, including data quality and validation practices
• Experience in deploying software using CI/CD tools such as Azure DevOps, Jira, Jenkins, etc.
• Experience developing microservices that support real-time data ingestion
• Experience developing software applications using relational and noSQL databases
• Ability to ensure data integrity across distributed and streaming systems
• Experience with monitoring, testing, and automation in large-scale data environments

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.