Data Engineering Trainee

Andersen is an international IT company and one of the leaders in outsourced software development. We create digital products for clients worldwide, with a strong focus on healthcare, e-commerce, banking, fintech and enterprise solutions. Working alongside global businesses allows our specialists to solve complex challenges, process massive volumes of data, and build scalable platforms used by millions of people.

A traineeship is more than just learning. It’s an opportunity to understand how modern data infrastructures are built, how information moves across systems, and how reliable data pipelines power business decisions and digital products.

The Data Engineering Traineeship at Andersen is an opportunity to develop practical data engineering skills, work with industry-standard technologies, gain hands-on experience with real-world data workflows, and join the company upon successful completion of the program.

Applications are open in Azerbaijan (in the office: Baku).

What we offer:

• 5 months: from your first day in the Lab to your first day on a commercial project.

• Full-time — 5 days a week, 8 hours a day: an intensive format designed to help you reach a professional level faster.

• A hands-on approach. You won’t just learn Data Engineering concepts — you’ll apply them while working on practical tasks, data pipelines, and business-oriented cases.

• Exposure to the full data lifecycle. From data ingestion and transformation to storage, orchestration, quality control, and delivery.

• More than Data Engineering. Learning a second technology is built into the program by default, helping you broaden your technical expertise and better understand how data engineering integrates with software development.

• Employment upon successful completion of the program.

Who we are looking for: People who are passionate about data, enjoy solving technical challenges, building scalable systems, and creating reliable foundations for analytics and business intelligence.

Requirements:

• English proficiency at Upper-Intermediate level or higher (verbal communication).

• A Bachelor's degree or equivalent in Computer Science, Data Engineering, Software Engineering, or a related technical field.

• Understanding of data modeling concepts, ETL/ELT processes, and data integration approaches.

• Experience with or knowledge of Big Data technologies such as Hadoop, Spark, or Hive.

• Strong SQL skills and basic knowledge of NoSQL databases.

• Understanding of data warehousing principles and familiarity with platforms such as Amazon Redshift, Snowflake, or Google BigQuery.

• Programming skills in Python, Java, or Scala.

• Familiarity with version control systems and collaborative development workflows (Git, GitHub).

• Understanding of scalable data pipeline design and implementation.

• Knowledge of data orchestration tools such as Apache Airflow.

• Understanding of data quality practices, including validation, monitoring, and consistency checks.

• Basic troubleshooting and debugging skills for data pipelines and processing workflows.

• Experience with cloud platforms such as AWS, Azure, or Google Cloud for data storage and processing.

• Ability to work with large-scale datasets, optimize performance, and ensure data security and reliability.

• A strong motivation to grow in Data Engineering and continuously explore new tools, technologies, and industry trends.

Nice to have:

• Experience participating in academic projects, hackathons, or technical competitions related to Data Engineering, Big Data, or Data Analytics.

• Familiarity with containerization technologies such as Docker and Kubernetes.

• Understanding of CI/CD practices and their application in data infrastructure.

• Knowledge of streaming technologies such as Apache Kafka or similar event-driven platforms.

What makes our traineeship great:

• Experienced mentors and regular feedback. You'll always know what you're doing well and what you can improve.

• A personal coordinator. They will help you adapt, answer your questions, and support you throughout the program.

• Real engineering challenges. Building data pipelines, integrating systems, processing large datasets, and working with cloud-based infrastructures.

• Transparent grades and clear growth paths. You'll always understand which skills will help you reach the next level.

• Our own learning platform. Courses, materials, and a knowledge base — all in one place.

• A strong Data community. Learn from colleagues, exchange experience, and grow professionally faster.

Apply now — we review every application.

Build the foundation behind modern data platforms: start your professional journey with Andersen Data Engineering.