Data Engineer (Manufacturing)

Covetus; Dallas (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Covetus is seeking an experienced data engineer with manufacturing or engineering client experience to design and maintain scalable pipelines for multimodal sensor data (video, LiDAR, GNSS, IMU and telemetry). You will own ingestion, synchronization, transformation and publishing of AI training datasets.

The role requires strong Python and SQL, cloud platforms, workflow orchestration, data quality and lineage.

Qualifications

• 5+ years of data engineering experience.
• Experience processing unstructured and multimodal data including video, images, LiDAR, GNSS, IMU and telemetry.
• Experience building pipelines for curated AI training datasets through ingestion, synchronization, transformation, validation and publishing.
• Strong Python and SQL skills with 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.
• 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.
• 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

5+ years of data engineering

Multimodal data processing

AI training data pipelines

Python

SQL

Distributed data processing

Cloud platforms

Data lake / lakehouse

Workflow orchestration

Version control

Data quality

Metadata and lineage

Schema management

Dataset versioning

Camera / LiDAR / GNSS / IMU pipelines

Data normalization and enrichment

Automated data checks

Performance optimization

Observability and cost control

Collaboration with AI/annotation/QA

Documentation of designs and SOPs

Job description

With Manufacturing or engineering client experience

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.
• 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.