Training and Internship

Data Engineer is a tech professional responsible for designing, building, and maintaining the systems and architecture that allow organizations to collect, store, and analyze data effectively. They ensure that data is clean, reliable, accessible, and structured in a way that data analysts and data scientists can use.

Key Responsibilities:

Data Pipeline Development: Build and manage ETL/ELT pipelines that extract data from various sources, transform it into usable formats, and load it into storage systems.

Database Design & Management: Design, implement, and optimize databases (SQL or NoSQL) to store structured and unstructured data.

Data Integration: Integrate data from multiple sources, including APIs, third-party services, and internal systems.

Infrastructure Management: Use cloud platforms (like AWS, Azure, GCP) and tools like Apache Airflow, Kafka, or Spark for data processing and orchestration.

Data Governance: Ensure data quality, security, and compliance with regulations such as GDPR or HIPAA.

Common Tools & Technologies:

Programming Languages: Python, Java, Scala, SQL

Data Warehousing: Snowflake, Redshift, Big Query

ETL Tools: Apache Airflow, dbt, Informatica, Talend

Big Data Tools: Hadoop, Spark, Kafka

Cloud Platforms: AWS, Azure, GCP

Containers & Orchestration: Docker, Kubernetes

Typical Background:

Degree in Computer Science, Engineering, Mathematics, or a related field.

Strong knowledge of databases, data modeling, and software engineering principles.