Creating comprehensive data pipelines, from data cleaning and transformation to aggregation and segmentation, adept at troubleshooting and bug fixing, enabling detailed and targeted data analysis for various purposes.

Data Cleaning: This is the process of preparing data for analysis by removing or modifying data that is incorrect, incomplete, irrelevant, duplicated, or improperly formatted. This is often the first step in any data analysis task. Data Transformation: This involves converting data from one format or structure into another. This could include tasks like normalizing data, aggregating data, or reshaping data. Data Aggregation: This is the process of combining data in a way that then presents a summarized version of the data. This could involve operations like calculating the sum, average, or count of a particular data field. Data Segmentation: By creating different datasets for various purposes, you have segmented your data based on specific criteria. This allows for more targeted analysis and can provide insights that are specific to each segment. Data Pipeline Creation: If you've automated these steps or created a repeatable process for performing these tasks, you've essentially created a data pipeline. A data pipeline is a set of actions that ingest raw data from disparate sources and move the data to a destination for storage and further analysis. Bug Fixing: This involves identifying, troubleshooting, and resolving issues in your data or code. This is a crucial step to ensure the accuracy and reliability of your data analysis.

●Proposed and implemented innovations in the company's service, significantly improving back-to-back communication with clients ●Automated data loading and unloading into PostgreSQL using REST APIs from various services ●Suggested and implemented enhancements to the company's web application to reduce manual work for employees, including scripting for the PostgreSQL database ●Engaged in Python coding, utilizing the pandas library, for data analysis, loading, unloading, and reporting using REST API.

● Administered the Hollyhope CRM system ● Handled data input, output, verification, and processing ● Completed assigned tasks in AMOCRM for transferring data from there to the Hollyhope CRM.

Responsibilities: Worked on a task to create ERP system for a furniture store and perform work with orders of customers of the store. Technologies: 1C: Trade Management 8 for Kazakhstan. Практика. Обязанности: Работал над заданием по созданию ERP-системы для мебельного магазина и выполнению работы с заказами покупателей магазина.      Технологии: 1С: Управление торговлей 8 для Казахстана.

Information Technology, Information Systems

EPAM

EPAM, Introduction to Python

Coursera, Programming for Everybody (Getting Started with Python)

EPAM

Coursera, SQL for Data Science

Coursera, Data Wrangling, Analysis and AB Testing with SQL

Databricks, Data Engineer