lang-uk/recruitment-dataset-candidate-profiles-english huggingface dataset:
Position: Data Engineer
Category: Data Engineer
Experience: 11 years | English: intermediate


Armenian based data engineer with more than 10 years of experience in DWH/BI projecs using MS BI, Oracle and cloud-native stack
Position: Data Engineer
Category: Python
Experience: 2.5 years | English: upper

- Successfully built and maintained highly available data pipelines for a large tourism company.

- Developed and implemented ETL processes that resulted in a 20% reduction in data processing time.

- Received recognition from senior management for exceptional teamwork, problem-solving skills, and dedication to delivering high-quality results.

- Led the development of an innovative software application for a business which provides driving exams, resulting in increased efficiency and improved student outcomes.

- Built and deployed complex data pipelines for multiple clients, resulting in more streamlined data processing and analysis.
As a Data Engineer at Vention, I have completed a variety of projects and tasks utilizing a range of technologies to build and maintain highly available data pipelines. In one project, I collaborated with the data science team to build a real-time data processing pipeline. This involved building and optimizing ETL processes using Apache Spark and Apache Kafka, as well as developing automated data quality checks using Python and SQL.

In another project, I led the implementation of a cloud-based data warehousing solution using Snowflake for a retail client. This involved designing the schema and developing ETL processes to move data from multiple sources into the data warehouse. I also implemented a scheduling and monitoring solution using Apache Airflow and Grafana.

My skills in data engineering include proficiency in SQL and Python, experience with Apache Spark and Kafka, and expertise in cloud-based data warehousing solutions such as Amazon Redshift and Snowflake.

Moving forward, I am eager to further develop my data analytical skills. I plan to take courses in statistics and machine learning to better understand the data being processed and to help optimize the pipelines for better performance. I am also interested in exploring new technologies such as Apache Flink and Apache Nifi to improve the scalability and efficiency of the data pipelines.
I want to work in a Project where they use cloud technologies especially AWS. I am looking forward to work in a very communicative and supportive team. I would be happy to work in a Big Data field.
Position: Data Engineer
Category: Data Engineer
Experience: 3 years | English: intermediate

Master degree in Information Technology in Azerbaijan.
Oracle Certified Associate (1z0-071).
Oracle Cloud Infrastructure Foundations Associate Certificate.
PCEP – Certified Entry-Level Python Programmer
As a Data Engineer, I bring extensive experience in SQL, Python, and ETL, with a track record of successfully managing and executing complex data projects. My expertise in data modeling and database design has helped me design efficient and scalable data architectures that have contributed to the growth and success of multiple projects.

Currently, I am expanding my skill set by learning Cloud, Kubernetes, and Big-Data technologies, demonstrating a commitment to continuous learning and development. My passion for working with data and solving complex problems motivates me to stay up-to-date with the latest tools and techniques in the industry.

I am a proactive team player with excellent communication skills and the ability to work collaboratively with cross-functional teams. I thrive in dynamic and fast-paced environments, and I am always looking for opportunities to innovate and optimize data workflows to deliver high-quality results.
Expecting flexible working hours.
Position: Data Engineer
Category: Data Engineer
Experience: 7 years | English: fluent


As a Data Engineer, I have completed various projects and tasks that involved working with Python, SQL, Apache Spark, Apache Airflow, and other technologies. Some of the projects that I am most proud of are:

•  Migrating data from an in-house environment to GCP cloud (or GCP to Azure Cloud) leveraging DataFlow, PubSub, BigQuery (DataBricks, Data Factory, Logic Apps)
•  Implementing a data cataloging, templating and governance system ground up before DBT was a thing.
•  Automating data pipelines using Apache Airflow as a successor to Apache Oozie. As of now, the Apache Airflow setup not only has dynamic tasks configured just from YAML files, but also auto-resolving dependency tree parsed from SQL.

My current role in the team is to lead the design and development of the data engineering solutions, mentor and guide the junior data engineers, collaborate and communicate with Product people to encourage data-driven decisions.
Position: Data Engineer
Category: Data Engineer
Experience: 2 years | English: fluent


As a Data Engineer, I have successfully connected and prepared data from multiple sources to ensure seamless integration and analysis. I have created and managed data storage solutions in various databases, including both relational and NoSQL systems. Additionally, I have designed and implemented a robust data warehouse to facilitate efficient data analysis.

In order to streamline the flow of data within our organization, I have developed ETL pipelines with workflow orchestration using both Airflow and Prefect. Furthermore, I have created custom Python libraries for internal use to improve our team’s productivity.

I also have experience in developing and deploying cloud solutions using both GCP & AWS platforms. This has allowed us to leverage the power of cloud computing to enhance our data processing capabilities. In addition to this, I have created sophisticated Docker solutions to improve the portability and scalability of our applications.
Position: Data Engineer
Category: Data Engineer
Experience: 11 years | English: fluent

Led the creation of comprehensive Data Platforms from scratch, effectively handling all aspects from data ingestion to Data Warehouse, Data modeling, and building both forward and reverse ETL pipelines.

Successfully deployed complex data-centric systems to production environments.

Handled and processed large-scale data sets, working with volumes in the range of hundreds of terabytes.

Successfully established and grew effective data engineering teams.

For one of the clients, I reduced Snowflake costs by up to 35% and AWS costs by up to 30%.

Initiated and implemented the use of DBT within the organization, enabling analysts to write their own data transformation pipelines.
As a Data Engineer, I have worked on projects in the Ad-Tech industry, handling high query volumes and managing terabytes of data for both SSP and DSP. I possess expertise in programmatic ads.
Tech: Scala, Python, Apache Spark, AWS, GCP. 
Both batch and stream data processing

Building Analytical Data Platforms from scratch for eCommerce companies. Model of a Data Warehouse.
Snowflake, DBT, Python, Go

Worked in Telecom as a Data Engineer. Building of Data platform to analyze the mobile network telemetry and predict the possible failures.

I have experience in migrating on-premise Data Warehouse and ETL into Cloud.

Having predominantly worked with startups, I deeply understand the importance of ownership, delivering fast results, and maintaining a problem-solving attitude. 

In addition to my data engineering expertise, I possess strong backend development skills in Python, Scala, and Go. I am also a beginner in Rust, continuously expanding my technical toolkit to adapt to evolving technologies and industry demands.

Overall, my diverse experience showcases my ability to deliver effective data engineering solutions using various technologies.

I'm looking for a job as a Senior/Staff Data Engineer or Backend engineer.
Position: Data Engineer
Category: Data Engineer
Experience: 3 years | English: upper


As a data engineer with 3 years of experience, I've worked extensively
with big data, including organizing data warehouses, optimizing
procedures, and utilizing tools such as SSIS packages. I'm also familiar
with the Azure Cloud platform. My proactive and confident approach to
problem-solving has helped me excel in my field, and I'm excited to
continue growing and exploring new opportunities.
Position: Data Engineer
Category: Data Engineer
Experience: 4 years | English: fluent


As a Data Engineer with an M.Sc. in Computer Science, I possess expertise in SQL, Python, data preprocessing, transformation, visualization, analytics, feature engineering, and modeling. I have experience building fault-tolerant, distributed, and scalable end-to-end data pipelines, and am committed to delivering effective solutions that help organizations leverage their data to drive meaningful insights and achieve their strategic goals.
Position: Data Engineer
Category: Data Engineer
Experience: 2.5 years | English: upper


As a highly skilled Data Engineer with a solid background in Data Analysis and Python Development, I possess a unique combination of technical expertise and industry experience. My proficiency in Python and SQL, in addition to hands-on experience with various tools and technologies such as Spark, AWS, Azure, Hive, MongoDB, Databricks, Snowflake, and PowerBI, enables me to effectively design, develop and implement data pipelines and business intelligence solutions.

I have a proven track record of success in building efficient and reliable ETL pipelines using Azure Data Factory, AWS and other tools, as well as in implementing robust business intelligence solutions using Power BI, SSRS, and dbt. I have completed the Google Professional Data Analytics course and am currently preparing to obtain Cloud certifications in AWS and GCP, further demonstrating my commitment to staying current with the latest industry trends and technologies.

I am an ambitious, results-driven professional who is passionate about leveraging data to drive business growth and success. I am confident that my expertise and experience make me an ideal candidate for any data engineering role and I am excited to contribute my skills to help organizations achieve their data-driven goals.
Position: Data Engineer
Category: Data Engineer
Experience: 6 years | English: fluent

Certified Azure Data Engineer
Certified GCP Data Engineer
As a Senior Data Engineer at GlobusAI, I have completed several projects and tasks that have contributed to the success of the company. My main responsibilities include designing and implementing analytics platforms, automating data preparation and deployment, developing ETL pipelines, and ensuring smooth client onboarding and data migration.

One of my notable achievements was designing and implementing an analytics platform from scratch, which led to a 10% increase in client retention. To accomplish this, I utilized a range of technologies such as Airflow, Azure Log Analytics, Azure Blob Storage, MongoDB, PostgreSQL, DBT, Superset, Python, and SQL. This platform enabled seamless integrations with third-party client services through the development of scheduled and event-driven data pipelines using Azure Functions, Airflow, Logic Apps, Azure Queue Storage, Sharepoint, and Python.

I also optimized the data preparation process for Superset dashboards by implementing dimensional modeling in the data warehouse, resulting in a significant 5-fold improvement in speed. By implementing Superset dashboards with DBT and Great Expectations, I proactively monitored and enhanced the data quality of the central data warehouse, leading to a 30% reduction in report errors.

As the Senior Data Engineer, I am responsible for leading and collaborating with the product and business teams to ensure successful client onboarding and data migration. Additionally, I have automated the deployment of Power BI dashboards using Azure DevOps, Power BI REST API, and Python, resulting in a 2-fold reduction in client onboarding duration.

In terms of future improvement, I am keen on further enhancing the efficiency and scalability of the ETL pipelines by implementing CI/CD pipelines for all ETL processes using Azure DevOps. I strive to stay updated with the latest industry trends and technologies and continuously improve my skills in cloud platforms such as Google Cloud and Azure. Additionally, I aim to develop expertise in advanced data analytics techniques and machine learning to drive more impactful insights and value from the data.

Overall, I am proud of the projects I have completed and the positive impact they have had on client retention, data quality, and automation. I am excited to continue my role as a Senior Data Engineer, driving innovation, and contributing to the success of the organization.
Good team, interesting projects, moderate payment
Position: Data Engineer
Category: Data Engineer
Experience: 3 years | English: fluent


As a Senior Data Engineer, I have: 

1. Designed and built pipelines to stream data from ERP Systems (SAP) using Apache NiFi to be consumed by a Last Mile Delivery application used to manage deliveries of the company. 

2. Ingested data from disparate sources such as SAP, Postgres, MongoDB, and MySQL into a data warehouse (Redshift) integrated with dbt to power transformations. 

3. Designed and implemented a real-time data pipeline to process semi-structured data to extract analytical points on game characters and players by integrating million raw records from the Riot Games API for League of Legends using Python, Spark, Databricks, and Azure Data Factory.

4. Collaborated with data scientists to extract and present analysis and recommendations using Power B.I. on 2 established and prospective customers, competitors, marketing channels, and resources to respond to rival marketing campaigns and improve unique selling points by 55%.

5. Developed a microservice with Microsoft REST APIs to organize and authenticate users and embedded Power B.I analytics into an application using the Django framework.

6. Managed the validation, documentation, and profiling of data to maintain quality and improve communication between teams.
Position: Data Engineer
Category: Other
Experience: 0 years | English: intermediate

Motivated and interested in learning. Experienced PC user. I learn new programs quickly and easily adapt to assigned tasks. I love to work with typesetting and formatting text. Also, I study programming languages HTML, CSS, and JavaScript. I want to realize myself in the field of IT.
As a Сomputer science teacher I effectively utilized Google Suite (Docs, Forms, slides, sheets, and calendars) and other computer software to create meaningful lesson plans.
Was responsible for the software of class computers, updated, and adjusted it as needed.
Managed the school website page and was responsible for its content.
Created systems for effective communication with parents and students.
Organized and conducted distance learning using Google Class, Learning apps, Vchy.ua, Kahoot, and Zoom platforms.
Held tournaments and quests in computer science.
Position: Data Engineer
Category: Data Science
Experience: 6 years | English: upper


As Data Engineer, I can able to data wrangling and cleaning (SQL & NOSQ),
make Machine Learning Models for specific areas using Python (libraries: Pandas,
Numpy, Scikitlearn, Matplotlib, etc), and data visualization interactive web apps
straight from Shiny, Panel, Tableu, such as:
1. Developing, implementing and maintaining data pipelines to support ETL
processes (using Talend, Jupyter) from multiple data sources like SQL
Server, PostgreSQL, Mysql, AWS S3, etc.
2. Experience with SQL, NoSQL (MongoDB), relational database design,
methods for efficiently retrieving data, as well as data
preparation/wrangling both on demand.
3. Collect and process raw data at scale (including writing scripts, web
scraping, calling APIs, Dockerfile, write SQL queries, etc.)
4. Be an active part in the development of innovation and strategy of a brand
or product.
5. Cloud Experience (AWS Glue and Sagemaker), Azure Data Factory, Azure
Data Lake.
Position: Data Engineer
Category: Data Engineer
Experience: 1.5 years | English: upper

Completed Courses:
1) Data Science Fundamentals by DataRoot Labs (October 2021)
2) Learn Python 3 Course by Codecademy (February 2021)
3) Analyzing Data with Python by edX (December 2020)
4) Python Basics for Data Science by edX (November 2020)
5) SQL for Data Science by edX (November 2020)
6) Practical Git: for Absolute Beginners(October 2021)
At this time helping as volunteer coordinator for students on Data Science Fundamentals course by DataRoot Labs.
While studying on Data Science Fundamentals, got basic knowledge/experience in the following:

1) Math Fundamentals for Data Science: Linear Algebra, Statistics&Probability
2) Practising basic Python algorithms & data structures, OOP  and Python libraries(numPy, matplotlib, pandas, sklearn) in Jupyter Notebook.
3) Supervised & Unsupervised Learning that included: labs on regression, classification, dimensionality reduction PCA for image, etc implemented in Jupyter Notebook.
4) Implemented project in PyCharm using template with a ready made structure and instructions. Created an app with DB using Postgres, DB and app interactions were done with the help of SQLAlchemy.  Created API methods and routes for app, used Flask for testing and Docker to deploy it.
5) The last project has been also implemented in PyCharm and Jupyter Notebook given a full working code example using any Kaggle data according to the preference. 
As data was initially clean, features were only label encoded
Trained the model using DecisionTreeClassifier(), RandomForestClassifier(), AdaBoostClassifier(), GradientBoostingClassifier().
Position: Data Engineer
Category: Python
Experience: 1 years | English: intermediate

Data Archiving Strategy:
Accomplishment: Developed a data archiving strategy using Python and SQL to move historical data from the primary database to a low-cost storage solution. This optimized the primary database's performance and reduced storage costs, resulting in 20% savings in infrastructure expenses.
Automated Data Testing Suite:
Accomplishment: Designed and implemented an automated data testing suite using Python's testing frameworks. The suite included unit tests and integration tests for data pipelines, ensuring the accuracy and integrity of data transformations. As a result, data-related issues were detected early in the development process, reducing the number of production incidents by 20%.
Automation and Scripting: Python is frequently used for automating repetitive tasks and writing scripts for system administration.
Data Analysis and Data Science: Python's libraries such as NumPy, Pandas, and Matplotlib facilitate data manipulation, analysis, and visualization.
System Administration: Linux administrators manage servers, configure networks, and ensure system security and stability.
Position: Data Engineer
Category: Data Engineer
Experience: 3 years | English: upper

Azure Data Engineer DP-203 certification
PCEP certification
PCAP certification
AWS, Azure cloud platforms.
Design and implement complex data workflows.
Experienced building data pipelines and applications at scale.
Experienced with Spark (PySpark).
DWH, Storage modeling and maintaining.
Excellent Python skills.
Team lead experience.

Software engineering and project management - Bachelor`s degree
Data Engineering project.

Please, do not suggest any web collecting/scraping project.
Position: Data Engineer
Category: Data Engineer
Experience: 6 years | English: upper

- PhD in Life Science;
- Certifications:
        AWS: Data Analytics Speciality, Developer Associate;
        Coursera: Deep Learning Specialization;
AWS Certified Data Engineer with 6+ years of experience in Data Engineering. Strong knowledge of data architecture, including data ingestion pipeline design, data modelling, machine learning and advanced data processing.

Technologies: Python, SQL, PySpark, AWS services (Redshift, Glue, Lambda, S3, etc), Azure (Data Factory, Synapse), Databricks, Kafka, Pandas, Sk-Learn, PyTorch, etc.

Certifications:
        AWS: Data Analytics Speciality, Developer Associate
        Coursera: Deep Learning Specialization 

Recent projects:
Project 1:
        Data from different sources were collected in Data Lake with real-time and batch data ingestion jobs, with following transformation and loading into Data Warehouse.
    • Optimized 3 modules in company's platform library that decreased data processing time for the R&D teams;
    • Decreased data processing time and reduced expenditures (from 10% to 120%) by splitting logic between Batch and Streaming mode;
    • Designed and automated QA dashboard that allowed to catch data issues on the earliest steps.

Project 2:
        Data Lake migration: The goal of the project is to build a Data Lake that allows to monitor and control product logistic and distributions. Our team developed and installed a Monitoring Solution to automatically detect potential issues with the product.
    • Designed and developed new advertise module that clusterizes incoming events into similar group and integrates with other services;
    • Deployed and supported architecture to detect product frauds that is now being actively used in more than 15 countries; 
    • Increased data reprocessing and fault tolerance by adding silver (intermediate) Data Lake in pipelines;
    • Provided leadership in a sub-team (4 engineers) for 6+ months;
    • Optimized ML models with accuracy increase up to 12% by implementing assembled models.
Position: Data Engineer
Category: Data Engineer
Experience: 5 years | English: upper


AWS-certified Data Solutions Developer with 4+ years of experience in DA and BI. Committed to helping companies resolve business challenges, design and implement data analytics solutions.
DWH: Redshift, PostgreSQL, MySQL
Data Lake: S3, AWS Lake Formation, Snowflake
Data integration: AWS Glue, Lambda, AirFlow, Talend
Programming: SQL, PySpark, Python
Data Visualization: Tableau, Power BI, Data Studio, AWS QuickSight
Position: Data Engineer
Category: Data Engineer
Experience: 1.5 years | English: intermediate


Beter Nov 2021 - ...
DB\BI Engineer 
-Developing etl pipelines for data loading from various sources (such as operational DB, S3
storage, APIs, Excel sheets). Technologies: MSSQL Server, Python, AWS, SSIS, Airflow
-Building a database architecture for OLAP cubes
-Aggregation of information to define metrics inside the data warehouse
-Development of own projects based on Docker for collecting information from websites and
automation of routine processes (Selenium)
-Processing of large data sets in cloud services (PySpark, AWS Athena, S3)
-Using elementary machine learning methods for processing time series data
- I will be able to develop my skill
- Complex and interesting projects where I will be useful
Position: Data Engineer
Category: Data Engineer
Experience: 2 years | English: upper

Implemented  Data Quality practice from scratch.
Implemented TDD in DataMart development.
Betting and Healthcare domain
Ingest data sets from multiple sources(web scrapping, API).
Collect metadata.
Data Quality Check.
Automate data pipeline (airflow).
Develop ETL and ELT Pipelines (Spark, SQL).
Data Lineage.
Position: Data Engineer
Category: Data Engineer
Experience: 5 years | English: upper


BI: design reports and all related stuff from creating ETL and data models to building visuals. Qliksens, PowerBI, SAP, ms sql, pl SQL.
Data Engineer: creating data pipelines using Python under orchestration of mwaa, design dwh's in Redshift, supporting ongoing flows. Python, AWS services, SQL.
Ready to consider offers with less salary, but with more tech stack, including Docker maintenance, Unix usage and etc.