Data Quality Engineer

Jole Overview We are seeking a highly skilled and motivated

Data Quality Engineer || Remote with 8+ years

of experience. If you're passionate about coding, problem-solving, and innovation, we'd love to hear from you!

About Us CodeVyasa is a mid-sized product engineering company that works with top-tier product/solutions companies such as McKinsey, Walmart, RazorPay, Swiggy, and others. We are about 550+ people strong and we cater to Product & Data Engineering use-cases around Agentic AI, RPA, Full-stack and various other GenAI areas.

Must-Have Skills Python (Advanced):

Ability to write clean, testable, automated scripts; experience with Pandas/NumPy; API integrations. SQL:

Strong query writing, optimization, data validation, and debugging. LLM & RAG:

Experience in building, testing, and validating large language model pipelines, retrieval-augmented systems, and embeddings workflows. Data Quality Frameworks:

Designing and implementing quality checks, validation rules, anomaly detection workflows. Data Fluency:

Strong understanding of structured & unstructured data, schema design, metadata, and lineage tracking.

Responsibilities Build and maintain scalable

data quality frameworks

across datasets, pipelines, and AI/ML platforms. Validate inputs/outputs of

LLM and RAG architectures

to ensure accuracy, relevance, and consistency. Develop automated

Python-based testing and monitoring scripts . Partner with data engineers, ML engineers, and product teams to strengthen data governance. Create dashboards, reports, and alerts for continuous data quality monitoring. Perform root-cause analysis and drive long-term corrective actions. Ensure compliance with internal data standards and client requirements.

Why Join CodeVyasa? Work on innovative, high-impact projects with a team of top-tier professionals. Continuous learning opportunities and professional growth. Flexible work environment with a supportive company culture. Competitive salary and comprehensive benefits package. Free healthcare coverage.