Data Engineer

Project details

Dallas, TX Salary: $130,000.00 USD Annually - $140,000.00 USD Annually Description:

Data Engineer (AI & Autonomous Systems Data Platforms)

Dallas, TX (Preferred) | Remote (EST or CST) Considered

Compensation: Up to $140,000 Base Salary

Employment Type: Full-Time

Our client is seeking Data Engineers to help build and scale the data foundation that powers next-generation AI and autonomous systems. This role focuses on developing robust data pipelines that process and curate large-scale multimodal datasets, including camera, LiDAR, GNSS, IMU, telemetry, video, and image data used for AI training and machine learning initiatives.

You will work closely with AI, annotation, quality, and platform teams to ensure high-quality, reliable datasets are available for model development and deployment.

Required Qualifications

Preferred Qualifications

Why Join?

Interested? Apply to directly to along with sending your Linked IN profile.

Our client offers a comprehensive benefits package that may include medical, dental, and vision coverage, 401(k) with company match, life and disability insurance, paid time off, paid holidays, wellness programs, and opportunities for professional growth and development. Benefits eligibility may vary based on employment status and location

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Job Facts: Contract Independent | On-site | USD $130,000.00 - 140,000.00 per year

Skills: Scalability, Technical Writing, Knowledge Transfer, Data Engineering, Video, Training, Publishing, Python, SQL, Data Processing, Cloud Computing, Storage, Data Lake, Workflow, Orchestration, Version Control, Data Quality, Meta-data Management, Management, Machine Learning (ML), Computer Vision, Advanced Analytics, Sensors, Collaboration, Data Science, Artificial Intelligence, Insurance, Privacy, Marketing

Reference: Dice Id: cxjudgpa | Position Id: 1157995

• Design, develop, and maintain scalable data pipelines for camera, LiDAR, GNSS, IMU, and telemetry data.
• Ingest, normalize, synchronize, enrich, and package multimodal datasets for annotation and AI model training.
• Build automated validation processes to ensure data completeness, integrity, calibration accuracy, timestamp alignment, format consistency, and overall dataset quality.
• Establish reusable data models, metadata standards, lineage tracking, and dataset versioning practices.
• Optimize pipeline performance, scalability, reliability, observability, and cost efficiency.
• Investigate and resolve data quality issues and pipeline defects.
• Partner with AI, machine learning, annotation, platform, and quality teams to support model development initiatives.
• Create and maintain technical documentation, operational procedures, and knowledge-transfer materials.
• 5+ years of professional Data Engineering experience.
• Experience processing and managing unstructured and multimodal datasets, including:
• Video
• Images
• LiDAR
• GNSS
• IMU
• Telemetry Data
• Proven experience building end-to-end pipelines that create AI training datasets through ingestion, synchronization, transformation, validation, and publishing processes.
• Strong programming skills in Python and SQL.
• Experience working with distributed data processing frameworks.
• Hands-on experience with:
• Cloud-based data platforms
• Object storage solutions
• Data lake and lakehouse architectures
• Workflow orchestration tools
• Version control systems
• Solid understanding of:
• Data quality management
• Metadata management
• Data lineage
• Schema management
• Reproducible dataset pipelines
• Experience supporting AI, machine learning, computer vision, autonomous systems, or advanced analytics initiatives.
• Background working with large-scale sensor or telemetry datasets.
• Experience building highly observable and production-ready data platforms.
• Work on cutting-edge AI and autonomous technology initiatives.
• Collaborate with highly skilled engineering and data science teams.
• Build large-scale data platforms that directly impact AI model performance.
• Opportunity to work remotely while supporting an industry-leading organization.
• Start: flexible
• Remote: onsite
• Location: Dallas, TX, US, US