Databricks Tech Lead/Data Analyst/ Engineer/

We are seeking a senior-level Databricks Tech Lead / Data Engineer / Data Analyst with extensive experience in data analytics, cloud-based data engineering, and large-scale data solutions. The ideal candidate will be proactive, technically strong, and capable of delivering scalable, secure, and cost-efficient data solutions on AWS.

Roles and Responsibilities:

• Design, develop, and implement scalable, secure, and cost-efficient data solutions on AWS using Databricks.
• Lead migration of data assets from on-premises to AWS, leveraging GenAI automation options where applicable.
• Develop PySpark applications to extract, transform, and aggregate data from multiple sources.
• Build data models and generate actionable insights to support business solutions.
• Identify, gather, and consolidate data from diverse sources, ensuring data integrity and relevance.
• Clean, transform, and prepare datasets using Python (Pandas) and SQL with thorough quality checks.
• Automate repetitive data preparation tasks to improve efficiency and scalability.
• Pretrain, fine-tune, augment, and optimize large language models (LLMs) for business applications.
• Operate independently, demonstrating initiative in problem-solving, risk management, and continuous improvement.
• Maintain clear documentation of data workflows, coding standards, and analytical methodologies.
• Collaborate with stakeholders and colleagues to clarify requirements, validate data, and co-create solutions.

Job Requirements:

• Minimum 10 years of experience as a Data Engineer, Data Analyst, or related role.
• Proven expertise in Databricks on AWS, PySpark, and Python.
• Strong proficiency in Python (Pandas, Scikit-learn, Matplotlib) and SQL.
• Experience with migrating data from on-premises to cloud environments.
• Familiarity with GenAI automation for data asset migration.
• Expertise in data modeling, ETL pipelines, and delivering data-driven insights.
• Ability to develop automated, scalable data workflows and maintain reproducibility.
• Bachelor's degree or higher in Computer Science, Engineering, or a relevant field.
• Strong critical thinking skills, problem-solving ability, and proactive approach to risk and issue management.