Education Requirement: Bachelor's DegreeKey Responsibilities:•Design, develop, and maintain scalable ETL pipelines for ingesting, transforming, and loading structured and unstructured datasets.•Analyze complex data structures and source-to-target mappings to identify opportunities for workflow optimization and automation.•Monitor and ensure data accuracy, consistency, and integrity across systems and platforms.•Implement data migration strategies to support application modernization and transitions across platforms or cloud environments.•Collaborate with analysts, data scientists, developers, and business partners to translate requirements into effective data engineering solutions.•Monitor pipeline performance, troubleshoot operational issues, and enhance reliability, scalability, and efficiency.•Document data flows, transformation logic, and operational procedures for maintainability and knowledge sharing.Required Skills & Experience•2+ Years Professional Experience •Hands-on experience with data analysis, ETL development, and data migration.•Proficiency in SQL, including writing complex queries, transformations, and performance tuning.•Familiarity with Python for data manipulation, scripting, and workflow automation.•Experience with ETL frameworks or orchestration tools such as Apache Airflow, Talend, dbt, or similar.•Understanding of data warehousing principles including dimensional modeling and staging architecture.•Exposure to cloud-based data platforms such as AWS Redshift, Google BigQuery, Azure SQL, or similar environments.Preferred Qualifications•Experience with cloud ecosystems such as AWS, Azure, or Google Cloud Platform.•Knowledge of big data technologies (Hadoop, Spark, or distributed processing frameworks).•Exposure to data visualization tools (Power BI, Tableau, Looker) and version control systems (e.g., Git).•Experience designing automated data workflows or integrating workflow orchestration tools.Core Skills & Competencies•ETL pipeline development & optimization•SQL & Python for data processing•Data modeling and profiling•Understanding of data warehousing concepts•Cross-functional collaboration•Problem-solving & root cause analysis•Ability to document technical processes clearly•Continuous improvement mindset