Job Description

About Innowave Tech

Innowave Tech is an Artificial Intelligence (AI) company offering solutions for the Semiconductor and Advanced Manufacturing industry. Utilizing deep industrial domain knowledge, proven experience, and innovation, we provide expert AI solutions and systems to address various industry pain points.

We are seeking a highly motivated and detail-oriented Data Engineer Intern to join our data team. In this role, you will assist in designing, building, and maintaining data pipelines and infrastructure that support data analytics and decision-making across the organization. This is an excellent opportunity to gain hands-on experience with real-world data engineering tools, workflows, and cloud platforms.

Key Responsibilities

Assist in developing and maintaining data pipelines using ETL/ELT tools. Support data integration from various internal and external sources into data warehouses. Work with structured and unstructured data to transform it into usable formats. Help ensure data quality, consistency, and availability across systems. Collaborate with data scientists, analysts, and engineers to support data needs. Document data workflows, schemas, and system processes. Monitor data pipelines and resolve any issues or failures.

Requirements

Currently pursuing a degree in Computer Science, Data Science, Engineering, or a related field. Basic knowledge of SQL and experience with a programming language such as Python, Java, or Scala. Familiarity with relational databases (e.g., MySQL, PostgreSQL) and/or data warehousing solutions (e.g., BigQuery, Redshift, Snowflake). Experience in C# development. Understanding of ETL concepts and data pipeline architecture. Strong analytical thinking and problem-solving skills. Willingness to learn and work in a team-oriented environment. Internship duration should be at least 3 months full time. Resume should indicate your forecasted internship dates.

Preferred Qualifications:

Exposure to cloud platforms like AWS, GCP, or Azure. Experience with data processing frameworks (e.g., Apache Spark, Airflow). * Knowledge of version control tools (e.g., Git).