Timofei Anashko
Data. Teams. Outcomes.

Timofei
Anashko.

Lead Data Engineer / Head of Data & Analytics

I have spent 8+ years building data-intensive, high-load systems and 5+ years in technical leadership. I design warehouses and ETL/ELT pipelines, automated experimentation platforms and forecasting models, and lead remote engineering teams. Expert SQL. My focus is reliable systems, straightforward architecture and measurable business outcomes.

8+ years in data systems · 5+ years of tech leadership
Open to opportunities
Timofei Anashko — photo from his personal collection
Based inVientiane, Laos
UTC+7

Remote work · International teams

Scale and impact

≈1Musers per hour

Analytics and traffic-distribution platform

up to 15direct reports

Within a 35-person engineering org

−96%in analytics infrastructure costs
≈$20,000saved every month

One outcome · AT-systems. In my final quarter, with no loss of analytics quality.

01 / Selected work

From challenge to outcome.

Data platforms, experiments and models that inform business decisions.

Data platforms / Experimentation

Analytics platform & continuous experimentation

Automated A/B testing · BigQuery · PostgreSQL · ETL/ELT

Challenge
Automate A/B testing and advertising traffic allocation around business performance.
My contribution
Designed an analytics and traffic-distribution platform with continuous automated A/B testing built in. BigQuery and PostgreSQL warehouse with ETL/ELT pipelines. Used conversions, revenue and profitability to evaluate variants and optimize traffic allocation.
Outcome
Platform scale: approximately 1 million users per hour.

Efficiency / Cost optimization

Making analytics more cost-efficient

SQL · BigQuery · Computation optimization

Challenge
Reduce analytics infrastructure spending while preserving analytical quality.
My contribution
Optimized analytical computations and the data platform at AT-systems.
Outcome
In my final quarter, analytics costs fell by 96% — approximately $20,000 saved per month, with no loss of quality.

Applied mathematics / ML

Predicting traffic ROI & profitability

BigQuery ML · ROI forecasting · Mathematical modeling

Challenge
Forecast the return on investment and profitability of advertising traffic using warehouse data.
My contribution
Trained and applied models directly in BigQuery ML, keeping the data in the warehouse. Developed custom mathematical models for the same prediction tasks.
Outcome
The custom mathematical models achieved higher accuracy than the ML models used for these tasks.

Architecture / Real-time bidding

RTB bidder (DSP) architecture

Projected · Project incomplete

RTB · DSP · System architecture · Reliability

Challenge
Design a bidding system around latency, reliability and operating costs.
My contribution
Designed the architecture of an RTB bidder (DSP) with a focus on response speed, system simplicity and lower operating costs.
Status
Projected cost reduction: ~90%. The project was not completed before I left the company; the figure remains a forecast.

02 / Experience

Building systems. Leading teams.

January 2021 — October 2026

AT-systems

AdTech & affiliate marketing · Remote

Team Lead / Tech Lead

Data Engineering & Analytics

Led data engineering and analytics: priorities, architecture, code review and team development.

  • Remote team of up to 15 direct reports within a 35-person engineering org: hiring, 1:1s and performance reviews.
  • Analytics and traffic-distribution platform handling ~1M users per hour; BigQuery and PostgreSQL warehouse, ETL/ELT.
  • Continuous automated A/B testing built into traffic distribution.
  • BigQuery ML and custom mathematical models forecasting ROI and profitability.
  • Cut analytics infrastructure costs by 96% (~$20k per month).
  • Reporting in Looker and Tableau.
  • Architecture of an RTB bidder (DSP); projected cost reduction of ~90% (the project was not completed before I left).
  • Event-driven architecture on Pub/Sub with BigQuery integration.
  • CI orchestration and code review with AI agents (Cursor, Codex, Claude Code).

2024 — 2026

Independent projects

Private repositories · access on request

Data & backend engineering

Go · BigQuery · GCP · Cloudflare

Self-directed projects across data engineering, backend development and LLM features.

  • LLM features in Go: a Claude-based assistant with tool calling, a Gemini classifier over gRPC, and content generation via Vertex AI.
  • Statistical anomaly monitoring in BigQuery SQL (shrinkage, EWMA, z-score) with a NestJS API.
  • Event traffic pipeline: Cloudflare edge, then Go ingest on Cloud Run, Pub/Sub (Avro, DLQ) and BigQuery raw / staging / marts with deduplication, bot flags and attribution.

2018 — 2020

LoveLife Co Ltd

Vientiane, Laos

Production accounting systems

Data engineering

Data and production accounting system for a food manufacturing business: structured operational data and automated processes.

Education2013

South Ural State University

Food production process engineer

03 / Expertise

Depth in data.
Breadth in engineering.

Data & BI

From query to platform.

SQL (expert), BigQuery, PostgreSQL / Cloud SQL, ETL/ELT and data modeling. Reporting in Looker and Tableau.

Experiments & models

Mathematics for business decisions.

A/B testing, BigQuery ML, ROI and profitability forecasting, statistical anomaly monitoring.

Engineering environment

Reliable systems, clear architecture.

GCP (Pub/Sub, Cloud Run, Cloud Scheduler), Cloudflare Workers, Go, TypeScript / Node.js, NestJS, GraphQL / React, Docker, gRPC. Python for scripting.

Leadership

From priorities to delivery.

Leading remote teams, hiring, 1:1s, performance reviews, prioritization, architecture and code reviews, AI-agent-assisted development.

Working languages

Russian — native · English — fluent

04 / Contact

Let’s talk.

Open to remote roles with international teams. I’d be glad to discuss challenges at the intersection of data, engineering and leadership.

Vientiane, Laos · UTC+7