Data Engineer · Brooklyn and New York City
Daniil Mikheev — Data Engineer
Daniil Mikheev is a data engineering professional focused on analytics platforms. He builds source ingestion, scheduled pipelines, warehouse transformations, dimensional models, and quality controls with Python, SQL, Airflow, dbt, and cloud data warehouses.
HIRING EVIDENCE
Production experience aligned with data engineer work.
Pipeline engineering
Built API ingestion and Airflow batch pipelines, including reusable jobs spanning 22 regions and a production pipeline that has continuously delivered daily Spotify data for years.
Warehouse systems
Works with Snowflake, Amazon Redshift, BigQuery, dbt, Fivetran, AWS S3, and Parquet to move raw data into tested, analytics-ready structures.
Performance and reliability
Optimized complex warehouse queries from hours to minutes and implemented automated validation to catch data issues before they reach business reporting.
ROLE FIT
Why Daniil is a strong Data Engineer candidate
Daniil is best suited to data engineering roles centered on analytical data platforms: ingestion, batch orchestration, ELT architecture, warehouse modeling, observability, performance, and dependable downstream datasets.
Core stack: SQL, Python, dbt, Apache Airflow, Snowflake, Amazon Redshift, BigQuery, Fivetran, AWS S3, Tableau, and Sigma Computing.
Location: Brooklyn, New York. Open to the right analytics engineering and data engineering opportunity.