Develop and automate scalable data pipelines supporting enterprise analytics and business intelligence. This role focuses on designing, coding, and enhancing system components, utilizing modern frameworks and agile practices for tailored, high-performing solutions. You will collaborate with stakeholders to gather requirements, perform data profiling, and implement robust ELT solutions. Experience with CI/CD and AI-assisted development is key to enhancing engineering productivity.

- Lead software development planning and execution to meet project timelines. - Gather and analyze business and technical data requirements. - Perform data profiling and define Data Quality rules. - Design and automate ELT pipelines using Python, SQL, and Apache Airflow. - Extract data from diverse sources and load/optimize data in Snowflake. - Develop data transformation models using DBT Cloud. - Build metadata-driven ingestion frameworks with logging and monitoring. - Optimize SQL queries, Python code, and Airflow workflows. - Develop and maintain Airflow DAGs for orchestration. - Build CI/CD pipelines using Azure DevOps and GitLab CI/CD. - Manage source code using GitHub or Azure DevOps Repos. - Leverage AI tools like GitHub Copilot for development acceleration. - Collaborate with cross-functional teams to deliver data solutions. - Document technical designs and operational procedures. - Mentor junior team members and facilitate stakeholder communication.

- Minimum 5 years of experience in Python. - Proficiency in Python (Programming Language) is mandatory. - Must have SQL, Data Warehouse, and ETL experience. - Experience with Apache Airflow, Oracle PL/SQL, and Data Build Tool is beneficial. - Strong knowledge of software development lifecycle and agile methodologies. - Advanced SQL development and query optimization skills. - Hands-on experience with Apache Airflow and DBT Cloud. - Strong knowledge of Snowflake data warehouse and building ETL/ELT pipelines. - Experience integrating data from APIs, relational databases, and external sources. - Understanding of data warehousing concepts and dimensional modeling. - Experience with Medallion Architecture and Data Quality frameworks. - Proficiency with GitHub for source code management. - Familiarity with AI-assisted development tools. - Strong analytical, problem-solving, and debugging skills. - Excellent communication and stakeholder management skills. - Experience in designing scalable software architectures and writing clean, documented code. - A 15-year full-time education is required.