Qode
About the Role:
We are looking for an enthusiastic Campus Data Engineer who is eager to start a career in data engineering and analytics. The ideal candidate should have a strong academic background in computer science, data science, or related fields, with hands-on project or internship experience in data engineering concepts, cloud technologies, and programming. Key Responsibilities:
·
Assist in building and maintaining data pipelines for ingestion, transformation, and storage of structured and unstructured data. ·
Work with big data frameworks (Hadoop, Spark, Databricks) and cloud platforms (AWS, Azure, or GCP) to process large datasets. ·
Support data modeling, ETL/ELT development, and performance optimization tasks. ·
Write clean, efficient Python/SQL code to manipulate and validate data. ·
Collaborate with senior engineers and analysts to deliver high-quality data solutions for business needs. ·
Participate in data quality checks, testing, and documentation. ·
Learn and adapt to new tools and technologies in the data ecosystem. Required Skills & Qualifications : · Bachelor's or Master’s degree in Computer Science, Information Technology, Data Science, or related field. · Strong knowledge of Python, SQL, and data structures. · Familiarity with data engineering concepts such as ETL, data warehousing, and data modeling. · Exposure to big data tools (Hadoop, Spark, Hive, Kafka) through coursework or projects. · Basic understanding of cloud platforms (AWS, Azure, or GCP). · Strong analytical, problem-solving, and communication skills.
We are looking for an enthusiastic Campus Data Engineer who is eager to start a career in data engineering and analytics. The ideal candidate should have a strong academic background in computer science, data science, or related fields, with hands-on project or internship experience in data engineering concepts, cloud technologies, and programming. Key Responsibilities:
·
Assist in building and maintaining data pipelines for ingestion, transformation, and storage of structured and unstructured data. ·
Work with big data frameworks (Hadoop, Spark, Databricks) and cloud platforms (AWS, Azure, or GCP) to process large datasets. ·
Support data modeling, ETL/ELT development, and performance optimization tasks. ·
Write clean, efficient Python/SQL code to manipulate and validate data. ·
Collaborate with senior engineers and analysts to deliver high-quality data solutions for business needs. ·
Participate in data quality checks, testing, and documentation. ·
Learn and adapt to new tools and technologies in the data ecosystem. Required Skills & Qualifications : · Bachelor's or Master’s degree in Computer Science, Information Technology, Data Science, or related field. · Strong knowledge of Python, SQL, and data structures. · Familiarity with data engineering concepts such as ETL, data warehousing, and data modeling. · Exposure to big data tools (Hadoop, Spark, Hive, Kafka) through coursework or projects. · Basic understanding of cloud platforms (AWS, Azure, or GCP). · Strong analytical, problem-solving, and communication skills.