Data Engineering Internship

Job Title: Data Engineering Intern

Remote - Night shift (5:30 pm to 2:30 am)

As a Data Engineering Intern, you will have the opportunity to work closely with the data engineering team and gain practical experience in designing, developing, and maintaining data pipelines and infrastructure. You will contribute to the development and optimization of data storage,processing, and retrieval systems, enabling efficient and accurate data analysis. This internship will provide you with hands-on experience in the field of data engineering and exposure to various tools, technologies, and best practices.

Responsibilities

Designing and developing data pipelines: Collaborate with the team to design and implement efficient and scalable data pipelines, including data ingestion, transformation,

and storage.

Data infrastructure management: Assist in setting up and maintaining data infrastructure components such as databases, data warehouses, and data lakes. Monitor and optimize performance to ensure data availability and reliability.

Data integration: Integrate data from various sources and formats, ensuring data quality and consistency. Develop data integration workflows and scripts to automate data processing tasks.

Data transformation and modeling: Implement data transformation processes to convert raw data into structured formats suitable for analysis. Work on data modeling activities to support data analysis and reporting requirements.

Data quality and validation: Implement data validation and quality checks to ensure accuracy, completeness, and consistency of data. Identify and resolve data quality issues in collaboration with the data engineering team.

Documentation and collaboration: Document technical specifications, data flows, and processes. Collaborate with cross-functional teams, including data analysts and data scientists, to understand data requirements and support their analytical needs.

Performance optimization: Identify opportunities for performance improvement and optimization of data processing and storage systems. Propose and implement solutions to enhance system efficiency and scalability.

Stay updated with industry trends: Keep abreast of the latest developments, tools, and techniques in data engineering and related fields. Share knowledge and contribute to the teams learning and growth.

Requirements

Currently pursuing a bachelors or masters degree in Computer Science, Engineering, or a related field.

Strong programming skills in languages such as Python, Java, or Scala.

Familiarity with databases (SQL, NoSQL) and data modeling concepts.

Knowledge of data processing frameworks and technologies such as Apache Spark, Apache Hadoop, Git, Jupyter Notebooks, Docker,Splunk, Elasticsearch / Logstash / Kibana (ELK Stack) or Apache Kafka.

Understanding of data integration and ETL (Extract, Transform, Load) processes.

Proficiency in working with Linux/Unix environments and command-line tools.

Excellent problem-solving and analytical skills, with attention to detail.

Good communication and collaboration skills.

Self-motivated and able to work independently as well as in a team.

Previous experience with cloud platforms (e.g., AWS, Azure, Google Cloud) is a plus.