Senior Data Scientist & Data Engineer

In this role, you will be responsible for developing AI & Machine Learning models for various use cases such as classification, prediction, NLP, computer vision, and generative AI. You will work on fine-tuning and optimizing Large Language Models (LLMs) and developing AI agents, Retrieval-Augmented Generation (RAG) systems, and automation workflows. Your key responsibilities will also include designing, building, and optimizing scalable ETL workflows using tools like Informatica, SnapLogic, and AWS Glue. You will develop and maintain data pipelines for ingestion, transformation, and loading into data warehouses, as well as manage data warehouse clusters and AWS EMR for high availability, performance, and security. Additionally, you will write and optimize complex SQL queries and implement data quality checks and validation frameworks. As part of the collaboration & operations team, you will closely collaborate with data architects, analysts, and business stakeholders to deliver scalable solutions. You will automate workflows using Python, troubleshoot data-related issues in production environments, and ensure compliance with organizational data security standards. Required Skills & Expertise: - Experience with cloud AI services on Azure, AWS, or GCP - Familiarity with MLOps tools such as MLflow, Kubeflow, Docker, CI/CD pipelines - Understanding of RAG systems, embeddings, prompt engineering, and LLM evaluation - Exposure to GPU computing, distributed training, or ONNX optimization - Experience with computer vision, reinforcement learning, or multimodal AI models Data Engineering & Cloud Technologies: - Strong SQL expertise (query optimization, stored procedures, performance tuning) - Hands-on experience with Informatica for ETL development - Proficiency with SnapLogic for integration and data flow automation - Experience with AWS Glue and AWS EMR for large-scale data processing - Experience with data warehouse platforms such as Snowflake, Redshift, BigQuery - Strong programming skills in Python for scripting, automation, and data processing - Understanding of data modeling, data governance, and data quality frameworks - Familiarity with cloud platforms (AWS, Azure, GCP) and modern data services Additional Skills: - Excellent problem-solving abilities and analytical thinking - Strong communication skills for working in a global, cross-functional environment Preferred Qualifications: - Bachelor's degree in Computer Science, Information Technology, or equivalent discipline In this role, you will be responsible for developing AI & Machine Learning models for various use cases such as classification, prediction, NLP, computer vision, and generative AI. You will work on fine-tuning and optimizing Large Language Models (LLMs) and developing AI agents, Retrieval-Augmented Generation (RAG) systems, and automation workflows. Your key responsibilities will also include designing, building, and optimizing scalable ETL workflows using tools like Informatica, SnapLogic, and AWS Glue. You will develop and maintain data pipelines for ingestion, transformation, and loading into data warehouses, as well as manage data warehouse clusters and AWS EMR for high availability, performance, and security. Additionally, you will write and optimize complex SQL queries and implement data quality checks and validation frameworks. As part of the collaboration & operations team, you will closely collaborate with data architects, analysts, and business stakeholders to deliver scalable solutions. You will automate workflows using Python, troubleshoot data-related issues in production environments, and ensure compliance with organizational data security standards. Required Skills & Expertise: - Experience with cloud AI services on Azure, AWS, or GCP - Familiarity with MLOps tools such as MLflow, Kubeflow, Docker, CI/CD pipelines - Understanding of RAG systems, embeddings, prompt engineering, and LLM evaluation - Exposure to GPU computing, distributed training, or ONNX optimization - Experience with computer vision, reinforcement learning, or multimodal AI models Data Engineering & Cloud Technologies: - Strong SQL expertise (query optimization, stored procedures, performance tuning) - Hands-on experience with Informatica for ETL development - Proficiency with SnapLogic for integration and data flow automation - Experience with AWS Glue and AWS EMR for large-scale data processing - Experience with data warehouse platforms such as Snowflake, Redshift, BigQuery - Strong programming skills in Python for scripting, automation, and data processing - Understanding of data modeling, data governance, and data quality frameworks - Familiarity with cloud platforms (AWS, Azure, GCP) and modern data services Additional Skills: - Excellent problem-solving abilities and analytical thinking - Strong communication skills for working in a global, cross-functional environment Preferred Qualifications: - Bachelor's degree in Computer Science, Informa