AI Engineer

We are seeking an experienced AI Engineer to design, develop, and optimize scalable ETL/ELT pipelines for enterprise data ingestion, integration, and transformation.

Responsibilities:

• Design, develop, and optimize scalable ETL/ELT pipelines for enterprise data ingestion, integration, and transformation.
• Build and maintain data engineering workflows using Databricks, dbt, PySpark, SQL, and Python.
• Develop Data Lake, Data Warehouse, and Lakehouse solutions, including data modeling and incremental processing.
• Collaborate with business stakeholders to understand requirements, business processes, and challenges, and translate them into effective data and analytics solutions.
• Proactively communicate with business users and technical teams to clarify requirements, provide project updates, address issues, and ensure solutions meet business expectations.
• Ensure data quality, consistency, security, and governance through validation and automated testing.
• Prepare and integrate enterprise data to support BI, AI/ML applications, and advanced analytics.
• Develop AI/LLM solutions, including RAG, AI agents, API integrations, and intelligent workflow automation.
• Monitor and optimize data pipeline performance, reliability, resource utilization, and costs.
• Implement data orchestration, CI/CD, automated deployment, and monitoring practices.
• Collaborate with BI, AI, IT, and business teams to support solution delivery, user testing, documentation, and continuous improvement.

Requirements:

• 2–4 years of hands-on experience in Data Engineering, ETL/ELT, and enterprise data platforms.
• Strong SQL and Python skills, with practical experience in Databricks, PySpark, Delta Lake, and dbt.
• Experience designing, developing, and optimizing production data pipelines, data models, and Lakehouse/Data Warehouse solutions.
• Ability to understand business processes, gather and clarify requirements, and translate business needs into actionable technical solutions.
• Strong verbal and written communication skills, including the ability to explain technical concepts to non-technical stakeholders.
• Strong analytical, problem-solving, and interpersonal skills, with a proactive attitude and ability to collaborate across business and technical teams.
• Familiarity with cloud data platforms (Azure/Microsoft Fabric preferred), Git, CI/CD, and data quality practices.
• Understanding of AI/LLM technologies, API integrations, and AI-driven data processing or automation.
• Nice-to-Have: Experience with RAG, AI agents, vector databases, Power BI, or enterprise ERP systems.