Data Engineer

Veriipro; Dallas (TX); On-site; USD 120,000 - 170,000; Full time

Job summary

Veriipro in the United States is seeking a senior data engineer to design and maintain high-scale pipelines for camera, LiDAR, GNSS, IMU, and telemetry data, enabling efficient AI training data creation.

You will normalize, synchronize, and enrich multimodal data, implement quality checks, and collaborate with AI, annotation, quality, and platform teams to ensure reliable, observable, and cost-effective data workflows.

Qualifications

• 5+ years of data engineering experience.
• Experience processing unstructured and multimodal data (video, images, LiDAR, GNSS, IMU, telemetry).
• Proven ability to build pipelines for curated AI training datasets from ingestion to publishing.
• Strong Python and SQL skills with distributed data processing knowledge.
• Familiarity with cloud data platforms, object storage, data lake/lakehouse, orchestration, and version control.
• Knowledge of data quality, metadata, lineage, schema management, and reproducible pipelines.

Responsibilities

• Design, develop, and maintain scalable pipelines for camera, LiDAR, GNSS, IMU, and telemetry data.
• Normalize, synchronize, enrich, and package multimodal data for annotation and AI training.
• Implement automated checks for completeness, integrity, calibration, timestamps, formats, and dataset consistency.
• Create reusable data models, metadata standards, lineage, and dataset-versioning practices.
• Optimize pipeline performance, reliability, observability, and cost.
• Troubleshoot data defects and collaborate with AI, annotation, quality, and platform teams.
• Document technical designs, operating procedures, and handoffs.

Skills

Data engineering

Multimodal data processing

AI training data pipelines

Python

SQL

Cloud data platforms

Data quality & lineage

Job description

Must Have Technical/Functional Skills

• 5+ years of data engineering experience.
• Demonstrated experience processing unstructured and multimodal data, including video, images, LiDAR, GNSS, IMU, and telemetry.
• Experience building pipelines that create curated AI training datasets through ingestion, synchronization, transformation, validation, and publishing.
• Strong Python and SQL skills with experience in distributed data processing frameworks.
• Experience with cloud data platforms, object storage, data lake or lakehouse patterns, workflow orchestration, and version control.
• Knowledge of data quality, metadata, lineage, schema management, and reproducible dataset pipelines.

Roles & Responsibilities

• Design, develop, and maintain scalable pipelines for camera, LiDAR, GNSS, IMU, and telemetry data.
• Normalize, synchronize, enrich, and package multimodal data for annotation and AI training.
• Implement automated checks for completeness, integrity, calibration, timestamps, formats, and dataset consistency.
• Create reusable data models, metadata standards, lineage, and dataset-versioning practices.
• Optimize pipeline performance, reliability, observability, and cost.
• Troubleshoot data defects and collaborate with AI, annotation, quality, and platform teams.
• Document technical designs, operating procedures, and handoffs.