BENCH+ PROFILE

Evgeny

Data Engineer
Cloud data platforms, data warehouses, data lakes, ETL, batch and streaming ingestion, data quality, and data platform delivery across Azure, AWS, and GCP.

Senior Data Engineer with broad hands-on delivery across cloud data platforms, data warehouses, data lakes, ingestion pipelines, data-quality frameworks, BI monitoring, and deployment automation.

BEST-FIT USE CASE

Best suited for enterprise data platform initiatives involving cloud lakehouse or warehouse engineering, upstream system onboarding, batch or streaming ingestion, PySpark transformations, data-quality controls, and release automation.

Not the primary fit: Less aligned with roles centered primarily on frontend delivery, mobile development, product ownership, manual QA, cybersecurity operations, or model training.

EVIDENCE HIGHLIGHTS

What supports the assessment

Set up cloud lakehouse storage, compute, batch jobs, SQL warehouse components, and distributed-processing checks for a tax-calculation migration prototype.

Designed streaming table pipelines and batch interactions with a messaging service in a cloud data platform.

Built ingestion pipelines into a cloud data lake using managed storage and orchestration services.

Engineered a cloud warehouse and BI dashboards for KPI monitoring and automated notifications.

Designed a monitoring-platform MVP on a cloud lakehouse stack and introduced deployment and release policies.

Engineered GCP-based data-lake ingestion, upstream system onboarding, and data-quality controls.

Integrated a cloud warehouse with a CRM-style upstream system using serverless, messaging, storage, and orchestration components.

Built an end-to-end performance monitoring solution using ETL jobs, a reporting database, BI dashboards, and automated notifications.

KEY STRENGTHS

Hands-on delivery of cloud data platforms across Azure, AWS, and GCP.
Practical experience with lakehouse, warehouse, and data-lake implementations.
Implemented ingestion pipelines and onboarding flows for upstream systems.
Built data-quality frameworks, monitoring datasets, BI dashboards, and automated stakeholder notifications.
Worked with both batch and streaming-style data processing patterns.
Combined data engineering with architecture, modelling, release-policy, and deployment-pipeline responsibilities.
Experience supporting production incident resolution and infrastructure automation around data platforms.

PRIMARY SKILLS

Data EngineeringCloud Data PlatformsDatabricksPySparkSQLETLData WarehousingData LakesAzure Data FactorySnowflake

ADDITIONAL TECHNOLOGIES

Power BIPostgreSQLOracleSQL ServerBigQueryRedshiftAirflowKafkaTerraformAzure DevOpsDockerData Vault 2.0

INDUSTRY EXPERIENCE

AI / DataEnterprise SoftwareHealthcareFintechRetailInsurTechTravelTelecomSaaS

ROLE MATCH

Data EngineerStrong

Data / ML EngineerPartial

Database EngineerPartial

DevOps / Platform EngineerPartial

Solutions EngineerPartial

Evgeny

Data EngineerCloud data platforms, data warehouses, data lakes, ETL, batch and streaming ingestion, data quality, and data platform delivery across Azure, AWS, and GCP.

Best suited for enterprise data platform initiatives involving cloud lakehouse or warehouse engineering, upstream system onboarding, batch or streaming ingestion, PySpark transformations, data-quality controls, and release automation.

What supports the assessment

Data Engineer
Cloud data platforms, data warehouses, data lakes, ETL, batch and streaming ingestion, data quality, and data platform delivery across Azure, AWS, and GCP.