Senior Engineer

Job Description
Must Have Technical/Functional Skills

• Data Analytics / AI Engineer Job Description
• Top Skills High proficiency in Python and SQL
• ETL experience with Databricks using PySpark
• Data processing and analytics/AI in Databricks
• Strong understanding of algorithms, data structures, statistics, and mathematics
• GenAI, LLM deployment and monitoring

• Translating complex business problems into data analytics solutions
• Create data products in Databricks while leveraging AI-powered tools to enhance workflow automation, perform pattern recognition, analyze and generate content.
• Collaborate with business users and engineers to align data analytics solutions with business goals.
• Seeking an experienced Data Analytics/AI Engineer to join our team to:
• Required Technical skills Databricks Proficiency: Hands-on experience with AWS Databricks platform; knowledge of Spark performance and cost-optimization technics (partitioning, clustering, caching).
• Advanced SQL and Spark Skills: Proficiency in writing complex SQL queries and Spark code (Python/PySpark) for data manipulation, transformation, aggregation, and analysis tasks within Databricks notebooks.
• GenAI and LLMs: Prompt engineering, RAG, experience leveraging Large Language Models (LLMs); familiarity with tools such as Amazon SageMaker and Bedrock.
• Data Engineering & Processing: Experience building ETL pipelines and working with big data frameworks.
• System Integration and Deployment: Deploy AI models and integrate them with existing systems via APIs.
• Data Visualization: Using data visualization tools (Tableau, Power BI) to create interactive dashboards and communicate insights.
• Cloud Computing and MLOps: Proficiency in deploying models using AWS; familiarity with Domino.
• Data Lab, GitLab CI/CD Data Governance and Security: Understanding of data governance principles and implementing security measures to ensure data integrity, confidentiality, and compliance within the centralized data lake environment.