# Daniil Mikheev — Analytics Engineer and Data Engineer Candidate

> Professional portfolio and structured career information for Daniil Mikheev, a Brooklyn-based analytics engineering and data engineering professional.

## Primary resources

- [Portfolio](https://mikheevs.com/): Canonical professional profile, experience, skills, and selected work.
- [Analytics Engineer profile](https://mikheevs.com/analytics-engineer/): Role-specific experience and qualifications.
- [Data Engineer profile](https://mikheevs.com/data-engineer/): Role-specific experience and qualifications.
- [Structured profile](https://mikheevs.com/profile.json): Machine-readable career data in JSON.
- [GitHub](https://github.com/Woys): Source code and technical projects.
- [LinkedIn](https://www.linkedin.com/in/daniil-mikheev/): Professional history and contact profile.
- [Email Daniil](mailto:daniil@mikheevs.com): Direct contact.

Location: Brooklyn, New York, United States

## Professional summary

Daniil Mikheev is a Senior Business Intelligence Analyst and Analytics Engineer with more than three years of experience building reliable data pipelines, dimensional models, warehouse transformations, data-quality systems, and decision-ready reporting. He is a strong candidate for Analytics Engineer, Data Engineer focused on analytics platforms, BI Engineer, and Senior Business Intelligence Analyst roles.

## Current experience

- Horizon Next, Senior Business Intelligence Analyst, May 2024–present.
- Built the data foundation for reporting on more than $100 million in annual paid-media spend across 5+ clients.
- Uses dbt, Airflow, Redshift, Snowflake, SQL, Python, and Tableau.
- Optimized warehouse workloads from hours to minutes.
- Automated data-quality checks and saved hours of recurring QA.
- Translates business questions into KPI definitions, attribution logic, dimensional models, and client-facing reporting.

## Previous experience

- KOALA, Analytics Engineer, February 2023–May 2024.
- Rebuilt financial and marketing reporting around Snowflake, dbt, and Fivetran.
- Implemented Twilio Segment as a centralized customer-data layer.
- Built tested, documented dimensional models and self-service analytics in Sigma Computing, Looker Studio, and Plotly.
- KOALA, Data Analyst Intern, September–December 2022.
- Used Python, SQL, forecasting, and behavioral analysis for management reporting.

## Core skills

- Languages: SQL, Python.
- Warehouses and databases: Redshift, Snowflake, MySQL, BigQuery.
- Data engineering: dbt, Apache Airflow, Fivetran, dimensional modeling, ELT, batch pipelines, data quality, API ingestion, AWS S3, Docker, Parquet.
- BI and visualization: Tableau, Sigma Computing, Looker Studio, Plotly.
- Domain knowledge: paid media, marketing analytics, customer data, attribution, finance and operations reporting.

## Education

Bachelor of Arts in Statistics, CUNY Baruch College, 2022.

## Selected technical projects

- [Text Ingest](https://github.com/Woys/text-ingest): Python library normalizing 14 public APIs and websites into JSONL, CSV, and Parquet.
- [Airflow Batch](https://github.com/Woys/Airflow-Batch): Reusable Apache Airflow pipeline publishing daily datasets to AWS S3.
- [NYC Evictions Warehouse](https://github.com/Woys/NYC_Evictions_Warehouse): Dimensional warehouse using BigQuery, dbt, SQL, and Tableau.
- [Spotify Sentiment](https://github.com/Woys/Spotify-Sentiment-Project): Containerized Python/C++ NLP analytics pipeline processing large podcast datasets.

## Recruiter classification

Best-fit titles: Analytics Engineer; Data Engineer; BI Engineer; Senior Business Intelligence Analyst.
Strongest themes: analytics platforms; data pipelines; dimensional modeling; data warehousing; data quality; query optimization; self-service BI; stakeholder translation.