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diyorbek ismoilov

@diyorbekismoilov

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I’m a data engineer specializing in Databricks lakehouse pipelines, governance, and client-facing delivery.

Poland

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What I'm looking for

I’m looking for a client-facing data engineering role in an agile team where I can build Databricks lakehouse pipelines, strengthen data quality/governance, automate validation, and deliver reliable metrics—on Azure and AWS—with strong documentation and stakeholder ownership.

I’m a data engineer with 5+ years of hands-on experience designing, deploying, and governing SQL- and Spark-based pipelines across insurance, sustainability, and e-commerce clients. I quickly grasp new business domains and adapt technical solutions to each client’s needs.

My work blends commercial Python, PySpark, and Databricks/Delta Lake to build Bronze/Silver/Gold lakehouse layers on both Azure (Synapse Analytics, ADLS Gen2) and AWS (S3). I focus on data quality and governance—source-to-target reconciliation, automated validation (pytest, Great Expectations), schema/access control, and lineage documentation for audit and compliance.

I’m also the regular bridge between engineering and business stakeholders. I translate ambiguous requirements into reliable pipelines, present findings to technical and non-technical audiences, and lead knowledge-transfer and documentation so client and business teams can operate independently.

I’ve led major migrations and performance improvements, including a legacy SQL warehouse migration with 100% data integrity at cutover and Spark/SQL optimization that reduced report or query times. I thrive in agile, fast-moving environments (Jira/Scrum) with shifting priorities and multiple concurrent workstreams.

Experience

Work history, roles, and key accomplishments

Senior Data Engineer

Risk & Insurance Analytics

Jul 2024 - May 2025 (10 months)

Built and maintained Python/PySpark pipelines on Databricks and Delta Lake to extract, transform, and validate insurance risk data from 6+ source systems, serving as the primary technical contact for business stakeholders. Led a legacy warehouse migration with source-to-target reconciliation and delivered automated QA using pytest and Great Expectations, reducing pipeline errors by 40%.

Python Pyspark Databricks Delta Lake SQL Data Validation Deduplication Data Quality Pytest Great Expectations Docker AWS S3 Query Optimization

Data Engineer

Plastic Recycling & Sustainability Platform

Sep 2023 - Jun 2024 (9 months)

Centralized data from 5+ sources into an analytics environment using Star Schema and built Bronze/Silver/Gold transformation layers on Azure. Implemented incremental ETL with automated testing and supported a full migration from on-prem SQL Server to Azure Synapse Analytics, including schema redesign, data cleansing, and historical load.

Star Schemas SQL Python Azure Synapse Delta Lake Bronze Silver Gold Layering Data Cleansing Data Migration Automated Testing Power BI Tableau MS SQL Server

Data Engineer

E-Commerce & Job Market Intelligence

Jul 2022 - Aug 2023 (1 year 1 month)

Designed Star Schema data models in PostgreSQL and built PySpark/SQL transformation pipelines for high-volume e-commerce and job-market data in an agile (Jira/Scrum) team. Built streaming-adjacent ingestion with Apache Kafka, investigated data discrepancies, and maintained production pipelines for recurring business reports.