Data engineer and analytics vision specialization

Job Summary

We are seeking an experienced Data Engineer with an Analytics and Computer Vision specialization to design, develop, and maintain scalable data pipelines and analytics solutions supporting image, video, and machine learning workloads. The ideal candidate will have strong hands-on experience with Python, SQL, Spark/PySpark, ETL/ELT, cloud data platforms, and computer vision technologies.

Responsibilities

• Design, develop, and maintain scalable data pipelines for structured and unstructured data.
• Build and optimize ETL/ELT workflows using Python, SQL, Apache Spark, and PySpark.
• Process and manage large-scale image and video datasets for analytics and computer vision applications.
• Develop data solutions supporting computer vision and machine learning workflows.
• Perform image and video preprocessing, transformation, and feature extraction.
• Work with OpenCV and other computer vision libraries as required.
• Design data models and data warehouse solutions for analytics and reporting.
• Optimize data pipelines for performance, scalability, reliability, and cost.
• Integrate data from multiple sources including APIs, databases, files, and cloud storage.
• Collaborate with data scientists, ML engineers, software engineers, and business stakeholders.
• Implement data quality, monitoring, validation, and governance best practices.
• Troubleshoot data pipeline and production issues and drive root-cause resolution.
• Use Git and CI/CD practices for code management and deployment.

Required Skills

• 10 years of experience in Data Engineering or a related field.
• Strong programming experience with Python.
• Advanced SQL skills.
• Hands-on experience with Apache Spark / PySpark.
• Strong experience building ETL/ELT data pipelines.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Experience with Computer Vision, Image Processing, or Video Analytics.
• Hands-on experience with OpenCV or similar computer vision frameworks.
• Strong understanding of data modeling and data warehousing concepts.
• Experience working with large-scale datasets.
• Experience with Git and CI/CD.

Preferred Qualifications

• Experience supporting Machine Learning / AI workloads.
• Experience with image/video data pipelines.
• Familiarity with ML frameworks such as TensorFlow or PyTorch.
• Experience with cloud-based data lakes and analytics platforms.
• Knowledge of Docker and containerized applications.
• Experience with real-time or streaming data pipelines.
• Strong communication and problem-solving skills.

Education

Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field, or equivalent practical experience.