Senior Data Scientist/Data Engineer

About the job

Job Requirements Key Responsibilities AI & Machine Learning Development · Design, build, and deploy AI/ML models for classification, prediction, NLP, computer vision, and generative AI use cases. · Fine-tune, optimize, and implement Large Language Models (LLMs) such as GPT, Llama, Falcon, or domain-specific models. · Develop AI agents, Retrieval-Augmented Generation (RAG) systems, and automation workflows. Data Engineering & ETL Development · Design, build, and optimize scalable ETL workflows using Informatica, SnapLogic, and AWS Glue. · Develop and maintain robust data pipelines for ingestion, transformation, and loading into data warehouses. · Manage and monitor data warehouse clusters and AWS EMR to ensure high availability, performance, and security. · Write and optimize complex SQL queries for data extraction, transformation, and reporting. · Implement data quality checks, validation frameworks, and data governance best practices. Collaboration & Operations · Work closely with data architects, analysts, and business stakeholders to understand requirements and deliver scalable solutions. · Automate workflows and operational processes using Python for improved efficiency. · Troubleshoot and resolve data-related issues in production environments. · Ensure compliance with organizational data security standards and industry best practices. Work Experience Required Skills & Expertise AI/ML & Advanced Analytics · 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 (serverless ETL) and AWS EMR for large-scale data processing. · Experience with data warehouse platforms such as Snowflake, Redshift, BigQuery, or similar. · 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 with the ability to work in a global, cross-functional environment. --- Preferred Qualifications · Bachelor’s degree in Computer Science, Information Technology, or equivalent discipline.

Requirements

• AI/ML
• Data Engineering
• SQL
• Informatica
• Python

Qualifications

• Bachelor's degree in Computer Science, Information Technology, or equivalent discipline

Preferred Technologies

• AI/ML
• Data Engineering
• SQL
• Informatica
• Python