Dmitrii Kurenkov

About Dmitrii Kurenkov

With over a decade of experience in data engineering, business intelligence, and data analytics, I specialize in creating efficient, scalable data solutions that empower businesses to make informed, data-driven decisions. I bring deep expertise in cloud platforms (Azure, AWS, GCP), ETL processes, and data visualization tools (Power BI, Tableau), paired with a strong command of SQL, Python, C#, and PowerShell.Throughout my career, I’ve developed and optimized data pipelines using tools such as Databricks, Azure Synapse, AWS Glue, and MS Fabric Spark Notebooks. I’m skilled at building data lakes, data warehouses, and integrating advanced analytics with platforms like Snowflake. Additionally, I leverage real-time processing frameworks like Kafka and Spark Streaming to support robust, high-performing data ecosystems.A results-driven collaborator, I enjoy working closely with stakeholders to translate business requirements into actionable data models and solutions. My experience spans industries and includes roles at Capgemini, Huron Consulting Group, and Avery Dennison, where I honed my ability to drive operational efficiency, manage complex data workflows, and mentor team members.If you’re looking for a data engineer with a proven track record in delivering end-to-end data solutions, feel free to reach out via LinkedIn or email me directly at d••••••••@gmail.com

Experience

1. Cloud Data Developer

   Capgemini

   Nov 2022 — Present · Los Angeles, CA, US

   Collaborated with clients to gather requirements and deliver status updates, ensuring alignment on project goals. • Managed CI/CD processes using Azure DevOps, deploying Azure Data Factory (ADF) and SQL updates in Agile sprints. • Ensured data quality through SQL data profiling, validation, and performance tuning of stored procedures. • Developed data pipelines with Databricks (PySpark), leveraging Pandas and NumPy for data manipulation. • Built data lakes using medallion architecture and optimized data warehouses for Power BI reporting. • Utilized ADF, Cosmos DB, and Synapse notebooks for ETL, storing transformed data in Synapse SQL pools. • Managed SQL data models with DBT, transforming and loading data into Snowflake for analytics. • Administered Snowflake environments, implementing row-level security and performance tuning. • Automated workflows with Azure Logic Apps and Function Apps, ensuring error handling and validation. • Implemented Databricks Unity Catalog for data governance and access control. • Migrated data from AWS S3/Redshift to Snowflake with AWS Glue and Apache Airflow for ETL jobs. • Wrote complex SnowSQL queries for data models, optimized for Power BI reporting. • Leveraged AWS Athena for data exploration on S3, enhancing analytics. • Developed ETL workflows with AWS Glue and Lambda for serverless processing. • Utilized MS Fabric Spark Notebooks for managing Lakehouse Delta tables. • Provided production support, resolving issues related to ADF, Databricks, SQL Server, and Power BI. • Optimized Azure Functions for ETL processes from databases and APIs. • Implemented Jenkins-based CI/CD for automating deployments and test-driven pipelines. • Processed streaming data with Kafka, Spark Streaming, and Hive for robust data pipelines. • Designed Power BI dashboards with DAX calculations and custom visualizations. • Improved Tableau performance, creating reusable templates for fast, consistent reports.