Data Engineering & Analytics Intern at Seamless.AI in Remote

Summary: Seamless.AI is a company that specializes in delivering AI-driven sales leads. As a Data Engineering & Analytics Intern, you will assist the Data Engineering team by building and optimizing ETL pipelines, performing data analysis, and improving data quality and scalability. Responsibilities: - Assist in building and maintaining ETL/ELT pipelines using Python and SQL - Clean, transform, and normalize structured and semi-structured datasets - Validate and monitor data quality across ingestion workflows - Perform exploratory data analysis (EDA) to identify anomalies and gaps - Analyze match rates, coverage issues, and enrichment performance - Propose data transformation improvements to increase precision and recall - Apply statistical reasoning to evaluate data quality, distribution shifts, and accuracy metrics - Write efficient SQL queries for analysis and transformation - Support performance improvements through query tuning and structured schema design - Work with large relational datasets - Document data flows, transformations, and validation logic - Contribute to improving internal data engineering best practices Required Qualifications: - Bachelor's degree required: Must be currently pursuing a B.S. in Information Sciences, Data Science, Computer Science, or a related field - Strong foundation in SQL and relational database design - Experience using Python for data manipulation and transformation - Understanding of ETL processes and data cleaning techniques - Familiarity with normalization, indexing concepts, and query optimization fundamentals - Comfortable thinking statistically about data quality, distribution shifts, and accuracy metrics - Strong analytical and problem-solving skills - Excellent written and verbal communication skills, with the ability to articulate complex data concepts clearly to technical and non-technical audiences Preferred Qualifications: - Coursework or projects involving end-to-end data analytics or ETL workflows, and exposure to data visualization or dashboard development concepts Required Skills: SQL, Python, ETL processes Important Skills: Data cleaning techniques, Data analysis Nice-to-Have Skills: Analytical skills, Problem-solving skills, Communication skills