Senior Data Scientist – AI, Data Engineering & Intelligent Automation

Own design, build, and maintenance of scalable ETL/ELT pipelines using PySpark, SQL, Delta Lake on Azure Databricks and manage data governance with Unity Catalog.

Lead development and deployment of AI and GenAI applications including Large Language Models, Agentic AI workflows, and RAG solutions across cloud/hybrid environments.

Engage with stakeholders to gather requirements, provide architectural guidance, lead technical discussions, and mentor junior team members.

6-8 years of experience in Data Science, Data Engineering, AI, or Analytics domains.

Mandatory skills: Python, SQL, PySpark, data pipeline development, ML modeling, AI platforms (OpenAI, Claude), and cloud platforms (Azure, AWS, or GCP).

Bachelor's degree in Computer Science, IT, Data Science, Engineering, Mathematics, Statistics, or related field; Master's degree preferred but not mandatory.

Experience with containerization (Docker), workflow orchestration (Airflow, Azure Data Factory), and version control (Git).

Experienced in end-to-end data engineering and AI solution delivery, capable of architectural decisions for scalable, production-grade systems.

Skilled in advanced analytics combined with AI/GenAI application development and deployment in enterprise cloud environments.

Comfortable bridging technical and business domains, leading teams, and translating complex technical concepts to diverse stakeholders.