Description

Design and develop AI-enabled data quality solutions and tools.

·       Build automated data quality, profiling, monitoring and anomaly detection capabilities.

·       Develop AI/ML and Generative AI capabilities to improve data quality and engineering processes.

·       Build scalable data warehouse and data engineering solutions to support AI use cases.

·       Develop APIs, backend services and user interfaces for AI and data quality applications.

·       Implement MLOps, CI/CD and monitoring practices for AI/ML solutions.

·       Collaborate closely with business, data and technology stakeholders.

Mandatory Skills:

·       Strong experience in Python, SQL and software development.

·       Good understanding of AI, Machine Learning, Generative AI and LLM concepts.

·       Hands-on experience with AI/ML frameworks and APIs.

·       Experience building data quality, data validation, profiling or monitoring solutions.

·       Strong understanding of data warehousing, data modelling and data engineering.

·       Experience with cloud data platforms such as Snowflake, Databricks, Redshift or equivalent.

·       Experience with AWS cloud services and cloud-based application development.

·       Experience with MLOps, model deployment, monitoring and lifecycle management.

·       Experience with CI/CD, Git and DevOps practices.

·       Experience developing REST APIs and backend services.

·       Experience with frontend technologies such as React, JavaScript or TypeScript.

·       Experience with data pipelines and orchestration tools such as Airflow.

·       Understanding of data governance, security and metadata management.

Good to Have Skills:

·       Experience with AWS Bedrock, SageMaker or equivalent AI services.

·       Experience with LLM, RAG and Agentic AI solutions.

·       Experience with vector databases.

·       Experience with PySpark / Spark.

·       Experience with Docker and Kubernetes.

·       Experience with Power BI or other BI tools.

·       Retail domain experience.

Traits / Abilities:

·       Strong problem-solving and analytical skills.

·       Strong ability to translate business needs into technical solutions.

·       Curiosity and willingness to learn emerging AI technologies.

·       Strong ownership mindset towards solution delivery and production support.

·       Ability to work across AI, Data Engineering and Technology teams.

·       Strong focus on data quality, reliability and governance.

·       Ability to work effectively in ambiguous and evolving environments.

·       Effective stakeholder communication.

Position Scope:

·       AI & ML: Experience developing and integrating AI/ML and Generative AI solutions.

·       Data Quality: Experience building automated data quality, validation, profiling and monitoring capabilities.

·       Data Engineering & Warehousing: Experience building data pipelines, data models and scalable warehouse solutions.

·       MLOps: Experience with model deployment, monitoring, versioning and CI/CD practices.

·       Full Stack Development: Experience developing APIs, backend services and frontend applications.

·       Cloud & DevOps: Experience with cloud platforms, Git, CI/CD and deployment practices.

·       Data Governance: Understanding of data security, governance, metadata and data quality standards.

·       Development Practices: Experience with Agile methodologies and SDLC.

·       Communication & Collaboration: Strong stakeholder management skills with experience in gathering requirements and presenting solutions.

Key Skills

Education

Any Gradute