lang-uk/recruitment-dataset-candidate-profiles-english huggingface dataset:
Position: Data Engineer / Machine Learning Engineer
Category: Data Science
Experience: 5 years | English: upper

I made a bounce from ETL Engineer to Data/ML Engineer within three months, mostly by self-development and self-learning.
I've successfully completed all the projects in which I was engaged, and I am sure that any of my former/current managers or customers will give a positive reference in case if it is requested. 
As well, I enhanced my English to the level of fluency which allows me to work with any customer without predicaments.
ML Engineer. Former DB/ETL developer with 6 years experience. 

Experience:
Grid Dynamics 
Data Scientist/ML Engineer 
June 2018 - Present 
Working in a small team on the chatbot platform: - Developing and improving models for NLP (Intent classification, NER, RE) - Developing text preprocessing - Gathering data for models and a catalog - Developing REST microservices - Handling data extracting and loading
Technologies: - Python (flask, requests, numpy, sklearn, keras) - JSON, HTML, CSV - MongoDB, ElasticSearch - Git, Jira, Scrum

Oracle DI/ETL Engineer March 
2017 - May 2018 (1 year 3 months) 
• Processing, integration, validating the big amount of data (100M+ rows) from different sources into Oracle DB (Exadata) • Designing and developing DB objects (tables, views, procedures, packages, indexes) • Tuning SQL queries, solving performance issues • Designing near real-time and batch ETL processes • Learning and practicing in Data Science
   
Technologies and tools: 
• Oracle Data Integrator • Oracle DB (Exadata) • MS SQL • BMC Control-M • Python • Pandas, Numpy • Matplotlib, Seaborn • Scikit-learn, stats • Git, TFS

Bell Integrator 
Senior Oracle Developer December 
2014 - March 2017 (2 years 4 months) 
Working on projects of "National settlement depository" (Russia) • Developing, maintaining, debugging PL/SQL procedure packages for complex depositary IS • Designing DB objects (tables, triggers, indexes, views, functions) • SQL query tuning • Developing ETL integration processes between different DB (Oracle, MS SQL, web services, files, e-mail)
Technologies and tools: • Oracle Database • SQL, PL/SQL • Oracle Data Integrator • Jython • TeamCity • Redmine • Git

I possess profound expertise in Data Analysis, ETL, Oracle, and Databases. I am seeking an opportunity for relocation and professional growth with the company.
Any relevant opportunity will be considered within adequate rates and conditions.
I will be happy to chat and stay in touch for further opportunities.
I am a dedicated employee, and I expect to dip into the environment in which I could be able to grow with the company and improve my skills. 
Also, I will be more than happy to work with a manager/team leader from whom I could learn.
Position: Data Engineer / MLops
Category: Data Engineer
Experience: 7 years | English: fluent

- has built custom MLops tool for automatic deployment, scale and monitoring gathering for TOP 3 Singapore bank in 6 month; 
- led a team of 4 middle data engineers; 
- successfully built Data Operations pipeline and/or infrastructure for over 10+ clients capable of handling TBs of data flow, preprocessing and storage;
Seasoned Python developer with 7 years of experience in extracting, manipulating, and storing large data streams using cutting-edge tools such as Spark, Airflow, and Kubernetes, alongside Pandas, Numpy, and TensorFlow. With a strong background in linear algebra, statistical and probability theory, has contributed to open-source KNIME workflows and is an active Kaggle contributor. As a certified Alteryx (SaaS) developer, possesses practical expertise in statistical techniques such as linear/logistic regressions, multivariate regressions, random forests, XGBoost, LSTM, and ARIMA. Has implemented MLops best practices for enterprises, including automated model deployment, model versioning, data drift, and performance monitoring. Has extensive experience in building ETL pipelines and has participated in public MLops events.
Can consider any type of products/services and become in alignment with team.
Position: Data Engineer / MLOps
Category: Python
Experience: 10 years | English: fluent


NDA - data warehouse and data science platform:
  Participated in the architecture of an on-premise data warehouse and data science platform, starting from defining technical specs for the bare metal machines.
 Created initial design of ETL migration from an in-house build system to open source
 Helped to set up development processes e.g.: code quality, the review process, on-boarding
 The main impact - I’ve initialized company “ETL”-mindset transformation, which helped to have much-complicated
analytics and insights generation.
 Impact: ​the whole ETL process had been improved, scaled up and automated, which gave the company the possibility
to scale up/down as much as it wanted. Performance for the running ETL processes increased in 2 times

NDA - machine learning productization system:
 Took lead in creating of the initial architecture
 Designed CI/CD pipeline to work with bare metal machines
 As a result of this project - the company started to use the on-line evaluation of the ml models instead of off-line one
 Impact​: Developed framework which helped to decrease ml model way to production from months to couple hours.
Insights Venture Partners - analytics platform:
 I played the main roles in system designs and was responsible for team building/hiring
 Helped to create ETL system which was generating meaningful insights for future investments

NDA - data aggregation:
 I played a key role in knowledge and project transfer from the other vendor, helped in code assessment and understanding of the definition of done for it.
 I was responsible for ETL processes revitalization - as a result I’ve increased speed and performance of the ETL into couple time
Position: Data Engineer / MS SQL developer / ETL
Category: SQL
Experience: 11 years | English: upper

Exam 761: Querying Data with Transact-SQL (2020)
15+ years of IT experience 

6+ years experience with huge databases (telecom and bank sector) 

 - New program modules development
 - Reports development
 - Troubleshooting legacy code
 - Data Base migration
 - ETL modules development
 - Data quality checking mechanisms development

 
Experience with small businesses databases (CRM systems)
 - SQL-Server administration (creating users, server audit, DB maintenance)
 - Development and optimization of server-side logic
 - Data Integration
 - Ad hoc reports
Position: Data Engineer on Python/Azure stack
Category: Data Engineer
Experience: 1.5 years | English: fluent

During previous project I was implementing LIBOR replacement package for several clients, who were pioneering new SOFR and SONIA based rates for asset evaluation.

Took part in 24/7 Support Service during Winter Youth Olympic Games 2020;
Assisted our Dev team during Sprint Demos;
Facilitated the retrospective sessions on behalf of PM;
Maintaining existing ETL-pipelines;
Created custom Azure Data Factory (ADF) pipeline to pull latest updates from a 3rd party provider into the ADLS(2) storage with pure ADF tools only, without relying on external notebooks or .jar libraries
Automated MS SQL backups recovery from local .bak files into .bacpacs and further downstream into Azure SQL Server via PowerShell scripted VM
Run some PoC researches on various data processing solutions like Dask, Databricks and Trino.
Prepared Power BI dashboard for the data platform on top of StarBurst cluster (a.k.a. Trino // a.k.a Presto) capabilities demo with underlying sql materialized views


Another project purpose was creation of universal Data warehouse for sport related events and organizations. We have communicated a lot with International Olympic Committee and their sport dictionaries. As a data analyst I was reviewing existing DB records, updated our Knowledge base on Confluence regarding new changes in Competitions and provided new mapping/ transformation rules for our Dev team.
To further develop as a Python Dev or Data Engineer. Look forward hands-on experience with industry accepted tools and approaches like micro services, blue green deployments, CI/CD pipelines and orchestrations.
Position: Data Engineer, Power BI Specialist
Category: Data Engineer
Experience: 2.5 years | English: upper

- Databricks Certified Data Engineer Associate 
- Astronomer Certification for Apache Airflow Fundamentals
- Microsoft Certified: Power BI Data Analyst Associate
- Microsoft Certified: Azure Fundamentals
- MongoDB Certified Associate Developer
- ITIL® 4 Foundation CPD
- Dataiku Core Designer
Experienced Data Engineer and Power BI specialist with a strong background in data modeling, ETL processes, data
integration and data visualization. Skilled in designing and implementing data pipelines and ensuring data quality and
integrity. Proficient in programming languages such as Python, SQL with expertise in various database technologies
(RDBMS, NoSQL). Collaborative team player with a track record of delivering data-driven solutions that drive business
growth and improve decision-making processes.

- 9 Years experience in retail banking
- Dozens of data pipelines (SSIS, Pandas, Airflow DAG's)
- Dozens of API's used
- More than 100 of Power BI, SQL and SSRS reports in production on Sales, Employee performance, Financial performance, Products, various KPI, Partners and etc.;
- Various automations in IT and business processes via Python, Telegram, command line.
What I do not expect:
- Any kind of work that demands frequent focus change between completely different spheres that is not even connected to Subject matter.
Position: Data Engineer (Python)
Category: Data Engineer
Experience: 3 years | English: intermediate


- Development of ETL/ELT pipelines 
- Integrating CI/CD practices (GitLab to Airflow)
 - Data visualization, creation analytical web applications/dashboards and tools
 - Creation of web services for data visualization and work with them
 - Producing prototypes to demonstrate concepts and ideas
 - Creating of internal web service for automation of tasks and optimization of work of SEO and marketing specialists with wide functionality
- Development of a data extraction system with 170+ connectors
- Development of systems for building reports
Prefer product companies with large amount of data
Remote working possibility
Flexible working schedule
Team of highly qualified professionals
Position: Data Engineer (Python)
Category: Data Engineer
Experience: 2 years | English: upper


More in CV upon request

Current Position:
Marketing Data Connectors SaaS Product Developer

Develop and maintain data connectors for a marketing-focused SaaS product.
Utilize Python, SQL, and Apache Airflow to create and manage ETL pipelines and orchestrate data workflows.
Previous Positions:

ETL and Data Streaming Pipeline Developer

Participated in the design and implementation of ETL and data streaming pipelines using NATS and JetStream.
Contributed to the open-source NATS JetStream Library, enhancing its features and improving its performance.
Developed infrastructure for efficient data storage and processing.
Async Telegram Bot Developer for an English School

Designed and developed an asynchronous Telegram bot for an English language school using Python and the aiogram library.
Hosted the bot on AWS and used PostgreSQL with SQLAlchemy for data storage, as well as Redis for caching.
Implemented complex testing and booking functionalities to streamline the user experience for students and administrators.
Position: Data Engineer / Python
Category: Data Engineer
Experience: 6 years | English: upper

Made batch and streaming loading Data Warehouses.
I've built ETL systems from start to finish in both Clouds oriented (GCP) and Server oriented formats.
Configure development and production server for the backend data pipeline on AWS instances (S3 bucket, RDS, Redshift).
Created the application architecture and DataBase that laid the foundation of the new app.
Certified Google Cloud Platform Professional Data engineer (Date of receiving January 11, 2022) 
The main domain of experience: Production, e-commerce, medical.

Worked on:
- Designing and creating ETL/ELT process and data infrastructure for product companies.
- Development of data pipelines and pre-processed data with dbt(Data Build Tool), Airflow including Hadoop.
- Made data analytics, building complicated reports with forecasting and data visualization (Metabase, Looker, Chartio, Tableau).
- Mainly work with Google Cloud Platform (BigQuery, Task, Functions, SQL, Dataflow, Spark, Composer, Pub/Sub) also, have experience with AWS (EC2, S3, RDS, Lambda, Redshift).
- Had been implementing logic for the Python backend (Django, Flask, Cloud Function) and JS frontend.
- Database and Data Warehouses design (PostgreSQL, MongoDB, BigQuery, MS SQL).
- Strong SQL data manipulation and processing expertise.
- Have working experience with Terraform and Ansible

Familiar with Agile and Scrum project management methods.
Worked with teamwork systems: Trello, Jira, Assana.
Used in teamwork: Slack, Google Meet, Discord, Microsoft Team.
I`m looking forward work with experienced software and data developers, and learning and implementing modern tools and technologies.
Expect to work with: GSP, Python, dbt / Airflow, engineering/tuning data pipelines, and data analytics.
Position: Data Engineer, Python dev.
Category: Data Engineer
Experience: 3 years | English: fluent

-- PostgreSQL, Clickhouse, MySQL, Snowflake, BigQuery, Redshift, Airbyte, DBT

-- Modeling relational databases (ER modeling, Relational schema, Normal forms), data modeling 3NF/Dimensional (Star/Snowflake)

-- Python, Django, FastApi, Pandas

-- k8s(Helm), Docker, Git (GitHub, Actions), Airflow, Metabase, Nginx, AWS/GCP 

-- Hadoop(MapReduce), PySpark(Datarbicks), TableFormats (Iceberg, Delta table), FileFormat(Avro,Parquet,ORC), Storage(S3,ADLS,GCS,HDFS)
TOP SKILLS:
-- PostgreSQL, Clickhouse, MySQL, Snowflake, BigQuery, Redshift, Airbyte, DBT, Dagster
--  Modeling relational databases (ER modeling, Relational schema, Normal forms), data modeling 3NF/Dimensional (Star/Snowflake,DataVault)
--  Python, Django, FastApi, Pandas
--  Metabase, Looker, Tableau
--  K8s(Helm), Docker, Git (GitHub, Actions), Airflow, Nginx, ElasticSearch, 
--  AZURE(Synapse, data factory, adls…)
--  GCP(Dataflow, PubSub, DataProc, Instance, GCS, BigQuery, …)
--  AWS(Glue, S3, EC2, Lambda, ElasticBeanstalk, IAM, VPC…)
--  Hadoop(MapReduce)Streaming, PySpark(Datarbicks), TableFormats (Iceberg, Delta table), FileFormat(Avro,Parquet,ORC), Storage(S3,ADLS,GCS)



---- September 2022 till now _ Itransition
---- Data Engineer role
1. Converting BigQuery queries to Snowflake after two companies merged
2. Doing ELT(dbt) with Snowflake-tasks, and for some SQL using Airflow. It depends on which team has 
created a ticket. 
3. Preparing semantic layer for Looker, so that Bi engineers(including me) can build dashboards 
and do some aggregations.
4. Building Looker reports and attaching them to business-related boards.
Python, Apache Airflow, GCP/AWS, Snowflake/BigQuery, Looker(LookML), SQL, DBT


---- September 2021 — September 2022 _ EPAM Systems
---- Python Engineer role
Extracting and data validation for RSS feeds.
Extending functionalities of existing lambdas.
Python, AWS(Lambda), S3, Elastic Beanstalk, VPC, EC2


---- August 2020 — September 2021 _ AlifTech
---- Data Engineer role
- Improved initially working with MySQL Tableau performance by replacing it with MongoDB.
- Wrote data pipelines using Apache Airflow (including data retrieving from several MySQL 
instances, processing them on Pandas, and storing them into MongoDB as data warehouse).
- Automated daily manual jobs with Airflow including sending daily reports to other departments.
- Automated ML model builds by refactoring code into Airflow DAGs and Tasks.
Airflow, python, pandas, FastAPI, Tableau
Position: Data Engineer/Python dev
Category: Python
Experience: 3 years | English: intermediate

A lot of automations that were made by me, really simplified and improved workflows on my projects.
I worked on different ETL processes, DB migrations, automatisation, many tasks were related to DevOps part.Have a pretty good knowledge of AWS.
I want to work in result driven collective/company where everyone wants to make an impact, to achieve goals.
Position: Data engineer, Python developer
Category: Python
Experience: 1 years | English: fluent

Looking for a remote job.
1 year in total of working experience as [big] data engineer
2 years of experience in technical support
1 year of working experience in front-end development
Looking for a job as big data engineer, would like to work the big data stack like: python, aws, spark, kafka
Position: Data Engineer/ Python developer
Category: Python
Experience: 6 years | English: fluent


Skilled in data engineering, machine learning and cloud engineering. Some of my previous work included:
- Designing and building data architectures and ETL pipelines on AWS
- Building and testing machine learning models for computer vision tasks, natural language processing & time series predictions
- Developing and deploying web apps in Python/ Django
- Data mining, cleaning and analysis
- Writing technical and end user manuals and documentations
- Configuring and managing cloud resources on AWS & GCP
- Configuring and managing distributed databases

Technologies/ tools: Python, AWS, Tensorflow, Apache Spark, PostgreSQL, deep learning, Git, 

Certifications: Coursera Deep Learning Specialization, Tensorflow certified developer (ongoing)
Education: MSc Electrical & Computer Engineering
Personal & professional growth
Position: Data Engineer/Python developer
Category: Data Engineer
Experience: 3 years | English: intermediate

Graduated Bachelor of Suleiman Demirel University (2020)
I am studying for a master's degree in Computer Science.
Successfully completed the "Big Data Engineer" training from Alfa Bank.
Currently, I work in the field of Data Engineering at Kaspi Bank. Developer DWH. We are consolidating data using big data tools like Pyspark, Apache Kafka, Hadoop. My task is to stream data from various sources and send it to DWH or another database.
We also work with cloud services like Google Cloud and AWS.
I want to develop further in this area and learn new technologies.
Position: Data Engineer / Python Developer
Category: Data Engineer
Experience: 2.5 years | English: upper

Master's Degree in Computer Science. A Data Engineer with experience managing digital media assets and data. Tools that I'm using the most: Python, Airflow, Azure, Snowflake, dbt, Postgres, MS SQL Server, Kubernetes, and Docker.
Product company (gambling field), Data Engineer
Oct 2022 - Present
1. Develop ELT pipelines for data source integration (Python, Airflow, Azure, dbt, Snowflake, Postgres, MS SQL Server, RabbitMQ, Kubernetes, Docker).
2. Develop data integration Python libraries (Python, Azure REST API, Power BI REST API).
3. DevOps responsibility: maintain and support K8S clusters, deploy microservices, setup and maintain CI/CD pipelines (Docker, Kubernetes, AKS, kubectl, helm, Lens, Gitlab, Azure)

One of the biggest outsourcing companies, Software Engineer
Feb 2022 - Sept 2022
Customer - the big UK company.
The goal of the project is to transfer data from external CMSs to the customer's own custom CMS. That requires writing rules using query transformation language and configuring pipelines for the data migration.
Participation:
1. Participated in the data migration cycle.
2. Developed JSONata transformation and mapping scripts for automating the pipeline.
3. Developed XSLT transformation and mapping scripts.
4. Performed testing phase for each of the process steps.
Database: MongoDB
Tools: jsonata, docker, mongoserver, GitLab, google services, Slack, Jira, Confluence
Technologies: YAML, JSON, git, go

One of the biggest outsourcing companies, Data Quality Engineer
Apr 2021 – Jan 2022
Customer - One of the biggest property and casualty insurers in the United States.
The goal of the project is to migrate the Customer’s DB2 databases to the Customer’s instance of AWS.
Technologies: Java, AWS, DB2, Spring boot, PostgreSQL, Bamboo.
Participation:
1.  QA/QC support of cloud migration activities
2.  Testing of databases objects: keys, sequences, triggers, tables, stored procedures, and user-defined functions
3.  Tests results analysis
4.  Regression testing
5.  Bug hunting and reporting
Less Talk More Action!
Position: Data Engineer / Python Developer
Category: Python
Experience: 3 years | English: intermediate

TD Feed Generator
- Service for generating various product feeds for integration with advertising accounts
TD Marketing Services
- Business process automation services of the Marketing Department
RealWeb — Python Developer (Part-time project) [Apr 2022 - present]
– Development of applications and services in Python
– Receiving and processing data from different sources

Technodom — Data Engineer [Jun 2020 - present]
– Development and support of existing ETL processes
– Collect and store data from analytic tools (Segment Stream, Google Analytics) and advertising systems
(Facebook, Google Ads, Yandex Direct and etc.)
– Import and export data from/to Google BigQuery, MSSQL, PostgreSQL, MySQL, SAP HANA and
BW
– Preparation and sending data to automated marketing systems
– Automation of business processes of the marketing department by developing new tools

Technodom — Loyalty Specialist [Dec 2018 - Jun 2020]
– Execution of the regulations of the ”TechnoBonus” Loyalty Program, automation of business processes
of the Loyalty Program in 1C CRM
– Development and control of execution of instructions and scenarios for the Loyalty Program in retail
stores and online stores
– Regular tracking and prompt correction of incorrect information in the CRM database
I want to: 
- Engage in tasks that include receiving, processing and storing data.
- Build a data pipeline and data warehouse architecture;
- Do tasks that include working with data visualization tools
Position: Data Engineer, Python Developer
Category: Data Engineer
Experience: 0 years | English: upper

EDUCATION
Kryvyi Rih National University
Master's degree with honours in Software Engineering
Graduated December 2022

CERTIFICATES
Google Cloud Certified Professional Data Engineer, September 2023
Relevant skills: BigQuery, BigTable, Dataflow, Dataproc, GCP, Pub/Sub

EPAM Systems Data Software Engineering (Big Data) Lab, October 2022	
Relevant skills: Apache Airflow, Apache Kafka, Apache Spark, HDFS
Audio-based identification of beehive states
• Developed a custom features extraction method with librosa and fine-tuned convolutional neural network with Keras to classify beehive states, achieving a classification accuracy rate of 99%.
• Used React to implement frontend and Flask for machine learning model deployment.

Excavator teeth condition control system
• Using Python with OpenCV and PyQt5 built a system that determines shovel teeth condition and informs the user regarding the status of each tooth.
• Gained fundamental knowledge of image processing by applying Gaussian blur, Canny edge detector, template matching, morphological operations, GrabCut algorithm.

URL shortening service
• Created a full-stack web application that allows users to shorten URLs and then manage them.
• Built a fronted with React, Redux, and Material-UI using modern practices with functional components and hooks.
• Utilized Firebase tools, such as Cloud Functions and Cloud Firestore for backend, Authentication to authenticate users to the app, and Hosting for deployment.

Sudoku Game & Solver GitHub
• Built an Android app on Kotlin to play Sudoku.
• Utilized knowledge of the Room persistence library to store Sudoku board data.
• Implemented a solver feature that uses a backtracking technique to find a solution to a game.
• Fulfilled features, such as autosave, undo, pencil marks, and auto error-checking.