Position: Analytics Engineer / Data Engineer / BI Developer…

@cyprusithr (Telegram MTProto) · 1 неделю назад
AI-саммари
Analytics Engineer / Data Engineer / BI Developer с опытом 7+ лет в построении платформ данных, ETL/ELT-пайплайнов, дата-мартов и BI-решений для fintech, retail, energy и mobile-продуктов. Сильна в автоматизации отчётности, SQL/Python-разработке, ML и аналитике бизнес-показателей; ищет удалённую full-time позицию.
Вертикали
finance
Трафик
native
ЗП от
не указана
Контакт
прямой
Площадка
@cyprusithr (Telegram MTProto) ↗
Обновлено там
03.08.2026
В базе с
15.08.2026
Оригинал с площадки RAW
Как пришло с «@cyprusithr (Telegram MTProto)» · скачано 15.08.2026 — без AI-обработки.
#CV #Analyst #AnalystEngineer #BI #Worldwide #Belarus #Russia #Remote
#CV #Analyst #AnalystEngineer #BI #Worldwide #Belarus #Russia #Remote 🧑‍💻 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: @tatiutiili Email: [email protected] LinkedIn: linkedin.com/in/tanya-borisik
свежие базы — в канале Подписаться на канал