Data Analytics Engineering Trainee
Indexed description
Join us to build or expand your skills through immersive, hands-on learning in three core areas:
- Data Integration. Master the art of developing and managing diverse data transformations and migrations.
- Data Visualization. Discover how to transform raw data into meaningful insights and present them through clear, engaging dashboards for better decision-making.
- Data Quality. Learn to ensure data is trustworthy, complete and accurate by testing the work of other data engineers, performing validations and re-creating logic to confirm it functions as expected.
Training process
The program is designed to guide you through two engaging stages:
Stage 1: Fundamentals (3 months with ~15-20 hours per week)
At this stage, you'll build a strong foundation in Data Analytics Engineering. Here's what to expect:
- Weekly learning. Explore self-study materials, then practice through tasks and tests. Each assignment will come with a one-week deadline, helping you make steady progress.
- Guidance from mentors. Submit your practical assignments for feedback and approval from experts on a weekly basis.
- Q&A sessions. Join weekly evening meetings to discuss your questions and gain professional insights. Recordings will be available.
- Skill assessments. Participate in 2 short individual assessments, including theoretical reviews and live coding exercises.
Stage 2: Specialization (4 months with ~20-30 hours per week)
This stage is all about taking your skills to the advanced level with a more intensive approach:
- Daily learning. Master in-depth materials and complete new practical assignments with further review every two days.
- Ongoing support. Attend daily group Q&A sessions with peers and mentors for real-time insights.
- Skill assessments. Participate in short individual assessments after each block, including theoretical reviews and live coding exercises.
General Requirements
- Citizens of Uzbekistan and permanent residents who are eligible to work in this country
- Second-to-last or final year university students and recent graduates
- Individuals aged 18 years and older
- English level from B2 (Upper-Intermediate) and higher
- Basic knowledge of Relational Database Management System (DBMS) theory
- Understanding of Structured Query Language (SQL)
- Familiarity with Python basics
- Degree from a technical university or other educational institution with a technical specialization
- Experience in banking and technical spheres
- Industry‑focused learning with EPAM, a leader in AI transformation engineering and consulting
- Free access to materials and resources designed and regularly refreshed by practitioners
- Intensive, hands-on training through numerous practical assignments
- Regular guidance and actionable feedback from professionals
- Modern educational ecosystem supported by built‑in AI tools
- Expansion of your core expertise alongside emerging technologies such as GenAI and Cloud
- Opportunity to join the EPAM team after successfully completing all stages
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