Data Engineer

About the Engineering Team

The Engineering team based in the US and Europe is responsible for the design development and deployment of the organizations core products with a focus on efficiency and speed. We architect and implement comprehensive solutions including tools and platforms to address key business requirements. These solutions encompass critical areas such as provisioning configuration continuous integration/continuous delivery (CI/CD) monitoring service level agreements (SLAs) performance optimization and system uptime. The team is committed to meticulous execution and collaborates extensively with a broad range of stakeholders throughout the product lifecycle.

What Will You Do:

As a Data Engineer you will be the backbone for our advanced AI/ML initiatives ensuring data is available reliable and scalable for model development and production.

Your tasks will include:

• Gather the data coming from the ERP into Snowflake design and build data pipelines: Architect construct and optimize robust ETL/ELT pipelines to ingest process and transform structured and unstructured data (including text images and multimodal datasets).

• Infrastructure for AI: Collaborate closely with Data Scientists to build and maintain the foundational data infrastructure and machine learning pipelines (MLOps) for deploying and serving AI/ML models in production environments.

• Data Integration: Integrate and manage data from various sources ensuring data quality reliability and accessibility across the organization.

• Cloud Deployment: Utilize cloud platforms (AWS GCP or Azure) to provision configure and manage scalable data storage and processing services.

• Vector Database Management: Implement and maintain vector databases (e.g. FAISS Pinecone) and data retrieval systems to support advanced Retrieval-Augmented Generation (RAG) architectures.

• System Optimization: Focus on performance optimization monitoring and system uptime for data services and integrated applications.

• Collaboration: Work with software engineers and data scientists to seamlessly integrate validated data and AI models into scalable core applications.

Qualifications :

Required Qualifications:

• Bachelors or Masters degree in Computer Science Data Science Engineering or a related field.

• 1 years of professional experience in a Data Engineering Software Engineering or MLOps-focused role.

• Strong programming skills in Python and experience with data processing frameworks (e.g. Spark Pandas Dask).

• Deep understanding of data engineering principles ETL/ELT pipelines and data modeling.

• Familiarity with data storage solutions including SQL/NoSQL databases and cloud solutions e.g. Snowflake.

• Experience with cloud platforms such as AWS GCP or Azure for data storage and processing deployments.

• Experience with CI/CD practices and deploying production systems.

Preferred Qualifications:

• Experience managing data specifically for NLP/LLM applications including text processing and embedding generation.

• Hands-on experience with MLOps tools workflow orchestration (e.g. Airflow Kubeflow) model monitoring and performance tuning.

• Experience with vector databases (e.g. FAISS Pinecone) and building retrieval-based data systems.

• Exposure to building data streams and real-time processing architectures.

Soft Skills:

• Good collaboration skills at all levels with cross-functional teams (especially Data Science).

• Highly developed ownership and creative thinking when solving data challenges.

• Analytical thinking and the ability to solve complex data and system problems.

• Process orientation and ability to build effective repeatable solutions.

• Time management and organizational skills.

• Fluent English language skills.

Additional Information :

About QAD:

QAD Inc. is a leading provider of adaptive cloud-based enterprise software and services for global manufacturing companies. Global manufacturers face ever-increasing disruption caused by technology-driven innovation and changing consumer order to survive and thrive manufacturers must be able to innovate and change business models at unprecedented rates of speed. QAD calls these companies Adaptive Manufacturing Enterprises. QAD solutions help customers in the automotive life sciences packaging consumer products food and beverage high tech and industrial manufacturing industries rapidly adapt to change and innovate for competitive advantage.

QAD is committed to ensuring that every employee feels they work in an environment that values their contributions respects their unique perspectives and provides opportunities for growth regardless of background. QADs DEI program is driving higher levels of diversity equity and inclusion so that employees can bring their whole self to work.

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race color sex age national origin religion sexual orientation gender identity status as a veteran and basis of disability or any other federal state or local protected class. 

#LI-Remote

Remote Work :

Yes

Employment Type :

Full-time