Data Engineer
Quality Ai
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Job summary
QualityAI is seeking a Data Engineer to design, build and scale data pipelines on cloud platforms, including Snowflake. You will collaborate with cross-functional teams to deliver AI-enabled data solutions and improve engineering practices.
The role emphasizes adaptability to evolving technologies and strong problem-solving skills. The ideal candidate will have hands-on experience with Snowflake and cloud data platforms, and a track record of delivering scalable data solutions in fast-paced
Qualifications
- Strong experience in Data Engineering with hands-on data pipelines design.
- Experience with cloud technologies (Azure, AWS or GCP).
- Hands-on Snowflake data platform experience.
- Experience with AI tools or AI-assisted development in data engineering.
- Able to adapt to evolving technologies and practices.
Responsibilities
- Design, develop, and maintain scalable data pipelines and data solutions.
- Collaborate with Software Engineers, DevOps, Product Owners and Data Scientists.
- Develop and optimize data solutions using cloud-based platforms.
- Build/maintain Snowflake-based data platforms and other cloud data platforms.
- Apply AI-enabled practices to improve automation and delivery.
Skills
Tools
Job description
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Qualitest is looking for Candidates for below :
Job Description – Data Engineer (AI & Cloud Data Platforms)
Role Overview:
We are looking for an experienced Data Engineer with strong expertise in cloud-based data platforms, modern data engineering practices, and AI-enabled engineering approaches.
The role will involve designing, developing, and maintaining scalable data solutions while collaborating closely with Software Engineers, DevOps teams, Product Owners, and other stakeholders
The ideal candidate should be adaptable to evolving technologies, have hands-on experience with cloud technologies and Snowflake, and understand how AI capabilities can be leveraged to improve data engineering processes and delivery outcomes.
Key Responsibilities:
Design, develop, and maintain scalable data pipelines and data solutions using modern data engineering practices.
Work collaboratively with Software Engineers, DevOps teams, Product Owners, Data Scientists, and business stakeholders.
Develop and optimise data solutions using cloud-based technologies and platforms.
Build and maintain solutions on Snowflake and other cloud data platforms.
Apply AI-enabled practices within data engineering, including leveraging AI tools and agents to improve development efficiency, automation, and delivery processes.
Explore and adopt emerging technologies to improve engineering practices and operational efficiency.
Support automation of development lifecycle activities using AI-assisted tools and intelligent engineering approaches.
Ensure data quality, reliability, scalability, and performance across data solutions.
Contribute to continuous improvement initiatives across engineering practices, standards, and ways of working.
Required Skills & Experience:
Strong experience in Data Engineering with hands-on experience designing and building data pipelines.
Experience working with cloud technologies (e.g., Azure, AWS, or GCP).
Strong hands-on experience with Snowflake data platform
Experience collaborating within cross-functional Agile teams including Software Engineering, DevOps, and Product teams.
Understanding of modern data engineering architectures and best practices.
Experience using AI tools, AI agents, or AI-assisted development approaches within data engineering.
Ability to adapt quickly to new technologies and evolving engineering practices.
Strong problem-solving skills with the ability to work in a fast-paced environment.
Desirable Skills:
Experience implementing automation within data engineering workflows.
Knowledge of CI/CD practices and DevOps principles.
Experience with data quality frameworks and testing practices.
Exposure to Machine Learning or AI-driven data solutions.
Experience working with large-scale enterprise data platforms
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