Position: Analytics Engineer / Data Engineer / BI Developer…
AI-саммари
Опытный Analytics/Data Engineer с 7-летним стажем в построении масштабируемых BI-решений и ETL/ELT-пайплайнов. Специализируется на автоматизации отчетности, оптимизации баз данных и внедрении ML-инструментов для повышения бизнес-эффективности.
- Грейд
- Senior
- Опыт
- 7+ лет
- Вертикали
- finance
- Трафик
- native
- ЗП от
- не указана
- Контакт
- прямой
- Площадка
- @cyprusithr (Telegram MTProto) ↗
- Обновлено там
- 14.09.2026
- В базе с
- 15.09.2026
SQL
Python
dbt
Greenplum
Superset
FineBI
ETL/ELT
TensorFlow
VBA
Data Modeling
Machine Learning
Data Warehousing
Оригинал с площадки RAW
Как пришло с «@cyprusithr (Telegram MTProto)» · скачано 15.09.2026 — без AI-обработки.
#CV #resume #opentowork #Analyst #AnalystEngineer #BI #Worldwide #Belarus #Russia
#CV #resume #opentowork #Analyst #AnalystEngineer #BI #Worldwide #Belarus #Russia
🧑💻 Position: Analytics Engineer / Data Engineer / BI Developer
📍 Format: Remote
⏰ Employment: Full‑time
💼 Experience: 7+ years
💰 Salary: Open to discussion
🧠 About me:
Analytics Engineer with 7+ years of experience in building scalable data platforms, BI solutions, and automated ETL/ELT pipelines. Worked across fintech, retail, energy, and mobile product environments. Proven ability to translate complex data into measurable business outcomes - from cutting reporting time by 95% to generating over $600K in annual savings through automation and ML. I embed AI tools (Cursor, LLMs) into daily development workflows, accelerating delivery by 40% while maintaining data integrity and stakeholder alignment.
⚙️ Key experience:
• Built automated dbt + Python pipelines replacing manual Excel reporting, cutting turnaround by 95% (4 hrs → 15 min)
• Engineered AutoCSI, a Python‑based AI scoring system for 500+ daily customer‑bot interactions, reducing QA time by 90% and improving CSAT by 8%
• Designed 30+ automated data marts (dbt) and 12+ FineBI dashboards, reducing reporting time by 93% (3 days → 2 hours)
• Optimized Greenplum SQL performance by 40%, cutting cloud costs by ~$200K/year
• Built P&L dashboards from scratch in Superset, improving budget decision speed by 40%
• Standardized KPIs across 5+ teams via a Metric Dictionary, eliminating reporting errors and improving decision speed by 30%
• Deployed a TensorFlow neural network for equipment pricing (Python), achieving <10% error and saving $500K+ annually
• Automated registry reconciliation with Python + VBA, saving ~$100K+ annually in labor costs
📊 Achievements:
• Drove 15% DAU and 18% MAU growth by diagnosing and resolving a critical verification bug, preventing $1M+ in potential revenue loss
• Reduced month‑end close by 40%, freeing 10+ hours/week and driving $600K+ in annual savings through live P&L insights
• Cut incident response time by 92% (3 hrs → 20 min) with 10+ Superset dashboards
• Mentored 5 analysts and developers, reducing onboarding from 4 months to 1 month (-75%) and boosting team delivery speed by 30%
• Improved forecasting accuracy from 15% to 7%, reducing stockouts/overstock by 20% and inventory turnover by 15%
🎓 Education:
• Applied Mathematics & Computer Science - Bauman Moscow State Technical University
🗣 Languages: Russian - native | English - C1/C2 (Fluent)
📬 Contacts:
Telegram: @tatiutiii
Email: [email protected]
LinkedIn: linkedin.com/in/tanya-borisik
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