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


1+ year of Java experience; 3+ years of experience in SAP projects, 1+ year in Change/Release Management. My skills: Java SE, Java EE, Hibernate, Spring, SQL, MySQL, JUnit, Maven, Git, HTML, CSS, ETL, DWH, SSAS, SSIS
More back-end and less front-end.
Position: Data Engineer
Category: Data Engineer
Experience: 2 years | English: fluent

Highlights: flattened Data Vault tables into one master table with automated feature generation powered by DBT macroses; migrated to Data Vault 10 pipelines including changes for 30 table, implemented comparison tests for old vs new approaches; written Python adapter for Hive metastore, etc.
•	2x AWS certified
•	Python, SQL, Snowflake, AWS, Azure, Airflow, dbt, MonteCarlo, Git, Docker
•	AWS Cloud Practitioner Certificate
•	AWS Data Analytics Certificate

RELATED
•	English: Advanced, IELTS 8.0 - C1
Remote work only
Position: Data Engineer
Category: Data Engineer
Experience: 4 years | English: fluent

NLP pet-project. I am working with the Ukrainian language corpus and improving the accuracy of the model released to Hugging Face. Speech-to-text API, exposed only to the Ukrainian language.

Master's degree in computer science. The master's work was in NLP. The main tasks made a summarization of short texts, by using extractive summarization methods. Used libraries/approaches - spacy, fasttext / LDA, word2vec, tf-idf.

I won a hackathon with a team of 3 members. Developed a website providing a 3D tour, that helps you to find a proper space for business, and rent it. I was responsible for the front-end part.

Responsible, calm, communicative, team player, and strong-willed. Interested in learning new technologies and obtaining unique experiences.
3.5 years of experience as a data engineer. I was engaged in complex analytical projects. 

/1 Created a pipeline that found chronic issues in IoT devices in 60% of cases. Helped detect problems in the early stage, and prevent bad customer experiences.
/2 Building and maintaining a number of software solutions for customers, related to data ingestion, processing, and building visual representation (dashboards) that enable data-driven business decisions and operational monitoring.
/3 Writing, execution, and maintenance of data transformation jobs, ETL/ELT using Spark and its API. Mostly Pyspark.

/4 Spam/fraud attack prevention. After accomplishing research, I found a new type of malicious website – that helped to detect fraud in the early stages.
/5 Data scraping and collection for further analysis. Used technologies: Scrapy + Python (requests, selenium), PostgreSQL, and AWS.
/4 Experience with NLP by extracting useful information from the text and working with ASR and text-to-speech processing.



- Languages:	Python, SQL, JavaScript
- Technologies: 	Azure(ADF/Synapse Analytics); Databricks, Postgres, BigQuery, ClickHouse, Git, ElasticSearch, Linux.
- Big data:	Hadoop, Spark, Airflow.
- Other: Docker; ML/NLP; OWASP; Sisense, Superset, Grafana; VS code, Postman.

Certification: Azure Data Engineer (DP-203)
Interesting and complex tasks. Professional growth in a team of professionals. Stable working conditions.
Position: Data Engineer
Category: Data Engineer
Experience: 1 years | English: fluent


- 3 years of commercial experience designing full-stack CRM & data processing applications with JavaScript/TypeScript/Node.js & relational databases. 

- 0.5 years of commercial experience building data-intensive analysis applications with Python (Pandas, Plotly dash, numpy).
Position: Data Engineer
Category: Python
Experience: 3 years | English: fluent

Successfully delivered complete IoT solutions that included data analysis,
multi-cloud infrastructure and embedded devices. 
Designed the architecture and implemented ETL data platform from scratch acting as Key Developer.
Successfully passed "AWS Certified Data Analytics - Specialty" and "Databricks Certified Associate Developer for Apache Spark" certifications
- 3 years of commercial  experience in Python/Cloud projects
- Experienced in all three major cloud providers: AWS, Azure and GCP
- Certified AWS Big Data Engineer
- Certified Spark Developer
- Experienced in major Big Data tools(Spark, Kafka, Hadoop)
- Bachelor's degree in computer science
- Fluent English writing and speaking skills

Interested in Big Data projects, preferably using AWS, Python and/or Scala.
Primarily interested in Big Data projects, preferably using AWS, Python and/or Scala.
NOT interested in Java, Web development, DBA, Android.
Position: Data Engineer
Category: Data Engineer
Experience: 4 years | English: upper


4+ years of professional experience in the Data / Machine Learning industry;
 Experience in development/modification of ML algorithms using Python programming language,
including on ML/DL frameworks;
 Experience in Python focused on Data Science and ML (Pandas, NumPy, Sklearn); 
 Experience with data visualization using Python-based libraries (Matplotlib, Seaborn, Plotly, 
Dash) and visualization tools such as PowerBI, Metabase
 Experienced with deep learning frameworks such as PyTorch, Tensorflow/Keras;
 Strong knowledge of SQL;
 Experience with AWS Data Analytics and Machine Learning stacks;
 MLOPS in AWS Sagemaker.
 Solid knowledge of statistics;
Solid knowledge of Snowflake
AWS Data Analytics stack
Position: Data Engineer
Category: Data Engineer
Experience: 5 years | English: fluent

Sped up Spark (AWS EMR) data pipelines by 30-70% with code optimization. 
Built dozens of integrations with different data platforms (APIs, databases, SFTP, S3), both for data ingestion and upload.
Designed and implemented data processing applications from scratch.
5 years of experience in building and maintaining ETL pipelines (partly freelance).
Advanced skills in Python, SQL, PySpark.
Extensive experience in debugging and performance profiling.
Result-oriented, attentive to details, good team player.

Stack:
Python, Airflow, PySpark, Flask, Superset
SQL (PostgreSQL, MySQL), Redis
AWS (EMR, Lambda, S3, CloudFormation, DynamoDB)
Linux, bash, Docker, git
Scrum, Jira, TDD
Position: Data Engineer
Category: Data Engineer
Experience: 6 years | English: upper


5+ years of professional experience in data processing and integration;
Experience in database/ETL architecture development;
The main domain of experience: e-commerce, b2c online services, online media;
Experience highlights:
-Solid SQL data manipulation and processing expertise;
-Database integration and ETL development;
-Deploying and maintaining ETL GCP services;
-Report Design (Tableau, Google Data Studio, PowerBI);
-Developing custom tools and approaches for data orchestration;
-Working with Linux environment;
-Managing data access for the DWH in GCP;
-Managing code-free ETL data integrations;
-Defining the strategy for DWH cost optimization;
-Feature engineering and model performance evaluation;
-Strong focus on automation and data-driven approach.
Position: Data Engineer
Category: Data Engineer
Experience: 6 years | English: upper


6 years of working experience in the IT industry as a Software Engineer, 3 of them as a Data Engineer. 2.5 years experience with Spark+Java+AWS, about a year experience with Spark+Scala+Hive. Solid knowledge of Java, Scala and Python are additional languages. Hands-on experience with SQL (PostgreSQL, MySQL) and NoSQL (HBase, Redis, DynamoDB).
Looking for challenging projects for professional growth, extending my experience to tech stack Spark+Scala/Python. Working in a team to be able to gain new experience and share the existing one.
Position: Data Engineer
Category: Data Engineer
Experience: 0 years | English: fluent


7 months of experience working as esports analyst for League of Legends teams, was responsible for gathering and analyzing data from the game, recognizing patterns, evaluating choices and presenting it to the team. 
2 months of experience as product analyst, used R as programming language, analyzed if customers use new functionality with events tracking data, made an interactive web dashboard with R shiny with refunds rate, orders and its categories.
Have hand-on experience with Looker and BigQuery via google cloud skills educational program and basics of google cloud infrastructue.
DataTalksClub DE zoomcamp with project required to get pass, hand-on experience with Mage, GCP, Azure, Terraform, docker, ETL, workflow orchestration.
Down to work with GCP and Azure, no experience with AWS.
Position: Data Engineer
Category: Scala
Experience: 8 years | English: upper

I am passionate about leveraging my expertise in big data technologies to drive business growth and streamline data-driven decision-making processes. With a proven track record of delivering high-quality data solutions on-time and within budget, I am confident in my ability to make a significant contribution to any organization
8 years work experience 
Proficient in Apache Spark Scala for distributed data processing and analysis
Experience with Apache Airflow for workflow management and scheduling
Knowledge of PostgreSQL for secure data access and management
Proficient Apache Hive and Oracle Databases for data storage and management
Strong skills in advanced data analytics techniques for distributed system
Led the design and development of a real-time data processing platform using Spark Streaming, resulting in a 50% reduction in data processing time.
Built and maintained data pipelines using Airflow, ensuring timely and accurate data delivery to downstream applications.
conducted extensive data analysis using advanced statistical techniques, resulting in actionable insights that drove business growth.
Passion and Interest:  driven by my  passion for a in data engineering field or industry. I actively seek opportunities that align with my interests and allow me to work in areas they are genuinely passionate about.
Position: Data Engineer
Category: Data Science
Experience: 1.5 years | English: intermediate


Accenture Latvia, AVS – M5 Command Center(ITA)
Data engineer(06/2017 – 05/2018)
 Support the Operation area through analysis and reporting on the operational data of the networking equipment,
the measurement of network performance (KPI) and the quality of the services provided by the IPTV product.
 Operate with critical identification objectives providing indications for continuous improvement of results.
 Support the customer by creating summary dashboards and system alarms derived from data analysis.
 Applications of the Splunk, Python, Shell, Postman products
 Universal Forwarder installation and configuration in Linux and Windows environments
 Indexer and Deployment Server installation
 Сonfiguration of new apps for monitoring data on machines
 Сonfiguration of monitoring rules for text and script files .sh, .py
 Integration of Postman, Python with the Splunk product for the monitoring of APIs exposed by the Accenture
Video Solution product

Accenture Latvia, SDWAN (US)
Data engineer (04/2017 – 06/2017)
 Creating dataset mockups and visualizations of SDWAN work.
 Using Python and Pandas library (Python) for preparing data
 Tableau for analyzing and visualization of SDWAN work.

Accenture Latvia, Intelligent Bench Analysis (LV)
Data engineer (02/2017 – 04/2017)
 Creating dashboard with information about projects, where candidates auto match for every project by Skills, Skill
level and etc. and for every employee matches information about projects where he can work with his skills.
 Developing application for auto updating Riga Project Dashboards in Splunk and exporting data from this
dashboards for analyzing. Using Bash Scripts, Python for developing and Splunk for analyzing and visualisation
data

Accenture Latvia, Flights (LV)
Data engineer (12/2016 – 02/2017)
 Create a service which can collect information about flights to different destinations and for different duration stay.
 Creating summary dashboard and system alarms derived from data analysis.
 Using Python for collect data from sites like Google flights. Flume for inserting data to Hadoop. Spark for
transforming and data analysis. Hive for data analysis. Qlikview for visualization results of data analysis. Splunk
for system monitoring and build alerts based on analyzed data
Position: Data Engineer
Category: Data Engineer
Experience: 3 years | English: upper

- Developed and optimized ETL pipelines using Azure Data Factory to efficiently ingest and transform data from multiple sources, improving overall processing speed and accuracy. 
- Implemented Slowly Changing Dimensions (SCD) approach for key dimensions, ensuring data consistency and historical tracking. 
- Enhanced data warehouse architecture by refining data models, adding new dimensions and fact tables, and streamlining existing tables to improve reporting and analytics capabilities. 
- Collaborated with cross-functional teams to identify and resolve data-related issues, providing support and guidance on data engineering best practices. 
- Designed and implemented data validation and error handling mechanisms, including logging and metadata tracking, to ensure data quality and maintainability. 
- Conducted performance analysis and optimization of stored procedures and ETL processes to improve query execution times and overall system performance. 
- Implemented and maintained Power BI dataset refresh processes, ensuring timely and accurate availability of data for reporting and analytics purposes. 
- Assisted in the migration of historical data from Excel to the data warehouse, developing data pipelines and table structures to accommodate the new data sources. 
- Contributed to the creation of onboarding and technical documentation, facilitating knowledge transfer and team collaboration. 
- Onboarded a Data Engineer from the client's team into our development process, responsible for reviewing her first onboarding tasks.
A highly skilled and experienced Data Engineer with a strong background in MS SQL, Azure, DWH, and ETL, seeking a challenging position to leverage my expertise in data engineering, data warehousing, and 
cloud technologies to deliver innovative solutions and contribute to the growth and success of a forward thinking organization.

Skills
Databases: MS SQL Server, Azure SQL Database
ETL Tools: Azure Data Factory, SSIS
Data Warehousing: Star Schema, Snowflake Schema, SCD, Kimbal approach
Cloud Services: Azure DevOps, Azure Blob Storage, Azure Key Vault, Snowflake
Languages: SQL, T-SQL, Python
Data Modeling: ER Diagrams, Dimentional Modeling
Reporting & Visualization: Power BI
Tools: Git, Idea, Visual Studio, Jira
Methodologies: Agile, Scrum, Kanban

My strong skills are responsibility, reliability, tolerance, sociability and patience. I am definitely a team player.
Position: Data Engineer
Category: Data Engineer
Experience: 5 years | English: fluent


Almost 5 years of my experience as a Data Engineer include:
* Designing and building ETL pipelines.
* Processing large-scale data with Apache Spark.
* Building Data Lakes.
* Tracing and eradicating inconsistencies and errors in pipelines.
* Agile development.

I have been responsible for the data engineering part of projects in domains such as advertisement, behavioral analytics and anti-money laundering.

My main technology stack includes but is
not limited to:
* Apache Spark (PySpark)
* Apache Airflow
* Oracle PL/SQL
* Apache Nifi
* Apache Kafka
* MinIO

Utilized programming languages are Python, Java and C++.
Position: Data Engineer
Category: Data Engineer
Experience: 4 years | English: fluent

Accomplishments:

AM-BITS LLC:

    Real-time Data Processing Leadership: Spearheaded the development of a real-time data integration system, leading to a 35% increase in data processing speed and achieving 99.5% accuracy in data integrations.

    Database Efficiency: Successfully migrated over 3TB of data from Oracle to PostgreSQL, resulting in a 25% improvement in query performance and a 15% reduction in infrastructure costs.

    Cloud Scalability: Migrated over 5TB of crucial datasets to cloud platforms (AWS S3 & Snowflake), realizing a 20% cost saving in storage expenses.

    Client Satisfaction: Guided a telecom client in their transition from Oracle to HDP, leading to a 30% cost reduction and a 90% satisfaction rate from the client.

MDM-Group:

    ETL Performance: Revamped and optimized ETL workflows with Apache Airflow, resulting in a 20% decrease in data latency and ensuring 24/7 data availability for analytics.

    Stakeholder Engagement: Integrated Apache Superset with the company's HDP stack, giving stakeholders real-time business insights which boosted data-driven decisions by 40%.

Kyiv Polytechnic Institute StartUp:

    QA Excellence: Identified and resolved over 150 platform discrepancies, ensuring optimal user experience for academic platforms.

    Automation Mastery: Implemented automated testing procedures with JMeter, reducing manual testing time by 45% and expediting the QA cycle by 30%.
AM-BITS LLC - Big Data Engineer (Apr 2021 - Present)

Real-Time Data Integration:

    Role: Lead Data Engineer.
    Tech: PySpark, Kafka, HBase.
    Details: Developed a real-time data system using PySpark & Kafka; enabled scalable storage with HBase.

Database Migration:

    Role: Data Engineer.
    Tech: PostgreSQL, Spark, Kafka, MongoDB.
    Details: Migrated data from Oracle to PostgreSQL using PySpark, Kafka, and MongoDB.

Cloud Migration:

    Role: Data Engineer.
    Tech: HDP, Apache Nifi, Hive, AWS S3, Snowflake.
    Details: Transitioned data to AWS S3 and Snowflake; aided a telecom client's transition from Oracle to HDP.

MDM-Group - Big Data Engineer (Nov 2019 - Jan 2021)

ETL Enhancement:

    Role: Data Engineer.
    Tech: Airflow, HDFS.
    Details: Optimized ETL workflows using Apache Airflow.

BI & Visualization:

    Role: BI Specialist.
    Tech: Superset, HDP.
    Details: Integrated Superset with HDP for real-time insights.

Kyiv Polytechnic Institute StartUp - QA Engineer (Aug 2018 - Feb 2019)

Academic Platforms QA:

    Role: QA Specialist.
    Tech: JMeter, Python.
    Details: Quality assurance for academic platforms using manual and automated testing.

Current Learning:
Enhancing skills in Tableau for better data visualization. Diving into Kubernetes for efficient model deployment.
Position: Data Engineer
Category: Data Engineer
Experience: 2 years | English: intermediate


Analytic and monitoring system of production lines:
• Applied Python frameworks (Pandas, NumPy, SQLalchemy) for Data manipulating
• Optimized the generation of weekly reports using SQL and Python, reducing time costs by 80%
• Created a concept of data visualization with Tableau which included critical KPIs and production metrics
• Implemented Airflow for scheduling data pipelines

Pet-project
Developed system realized with aiogram and Airflow that send daily messages to the user with information about new opened jobs, and weekly reports about the market dynamic based on user’s needs. System collects data about open jobs using API, extracts information from collected JSON files, transforms data to Data Frame and loads to PostgreSQL Database, then extracts new job positions and sends it to users.
Position: Data Engineer
Category: Python
Experience: 0 years | English: upper


An experienced bank manager with 10-year experience in bank/finance domain. Last 2 years on a position of head of a bank branch. Practical skills in analysis, planning, process optimization, problem-solving, negotiating, sales, communication with customers, handling meetings with customers. 
In 2018 attended courses of IT Business Analysis. Basic knowledge of different software development methodologies. Basic knowledge of modeling notations (UML, BPMN) and BA methodology and tools (functional/non-functional requirements, use cases, user stories, traceability). Basic knowledge in Python programming language. Experienced user of Microsoft Office.  

Eager to learn new things. Despite a lack of particular experience as a BA, hope to make a great contribution to the future team. My developed soft skills will help me to dive into technical details easily and within a short period of time.
Position: Data Engineer
Category: Data Engineer
Experience: 4 years | English: upper


Apr-2022 – Now(2023) - Big Data Software Engineer, SoftServe, 
Project: Implementing Data Warehouse in BigQuery
Team Size: Dev team - 5 DQ team - 1 DevOps - 2 Support - 2 PM - 1
Project Role: Developer
Tasks performed:
•	Support data pipelines running on production environment
•	Implement new data pipelines from various sources (SFTP/API/RDS)
•	Migrate old legacy pipelines to be more flexible/extendable and runnable on GCP ecosystem
•	Resolve incidents/change requests; communicate with requestors and users on daily basis
Environment:
•	GCP BigQuery
•	GCP Composer
•	GCR, GCS, GSM, Cloud Function

Nov-2021 - Mar-2022 - Big Data Software Engineer , EPAM Systems

Customer: EV - Other
Project: Augment client's team to build data lake in Redshift
Team Size: Dev team - 3 DQ team - 3 DevOps - 2 PM - 1
Project Role: Develop
Tasks performed:
•	Develop new ETL jobs.
•	Supporting old jobs, enhancing them with new requirements.
•	Communicating requirements with clients.
•	Refactoring solutions and proposing improvements, such as code, libraries, tools, etc.
Environment:
•	Redshift
•	AWS, Python, Serverless, Jenkins
•	AWS Lambda, EC2, S3, Glue, Athena, Redshift, AppSync

Feb-2020 - Oct-2021 - Big Data Software Engineer, EPAM Systems
Customer: EV - Other
Project: Reimplement Cloudera-based Big Data system in AWS
Team Size: Dev team - 3 DQ team - 3 Automations - 1 DevOps - 2 Support - 2 PM - 1
Project Role: Developer
Tasks performed:
•	Take an unstable on-premises PoC system and create a scalable production-ready platform within a cloud;
•	Delivery of API extensions to support numerous Customer’s Data Analytics applications;
•	Exponential system loads at the harvest time;
•	Use of variety of sources for genotype & phenotype data (varying from 10 rows to bills of recs);
•	Conduct technology assessment, select and deploy cloud-based toolkit for data scientist to extract high-volume data sets and run analytic & machine learning workloads;
•	Provide system stability during peak workloads (harvest seasons);
•	Contain operational costs;
Environment:
•	AWS - Aurora, Redshift, Glue Postgres for metadata and Airflow
•	AWS, Python, Airflow, Serverless, Jenkins
•	AWS Lambda, EMR, EC2, S3, Glue, Step Functions, Athena, Redshift, AppSync, Event Bridge Airflow, Postgres.
Position: Data Engineer
Category: Data Engineer
Experience: 2 years | English: upper


• Architected end-to-end AWS data pipeline and data warehouse
using AWS components such as Glue, Athena, Spark, S3, Lambda
functions, and EMR clusters.
• Engineered data warehouse using Hive, created and managed Hive
tables.
• Engineered spark code using python for faster testing and
processing of data.
• Modeled, aggregated, and triangulated multiple Log data and
populated to RDS data
• Devised high-performing data warehouse systems, optimizing
business intelligence and analytics.
• Managed life cycle elements of ETL development, from robust
testing to final deployment.
• Computed Machine Learning models (using Deep Learning,
Bayesian Networks, SVM), applied to balance and deploy
models.
• Extrapolated high dimensional health data.
• Developed briefs and curriculum for the Ministry of Health of Ethiopia
Position: Data Engineer
Category: Data Engineer
Experience: 3 years | English: fluent


A results-driven and experienced data engineer with 3 years of experience in the field, adept at designing, developing, and implementing robust and scalable data pipeline solutions. Possessing a strong technical background in programming languages such as Python and SQL, as well as hands-on experience with big data technologies such as Hadoop and Spark. A deep understanding of data warehousing principles and methodologies, and a proven ability to work with both structured and unstructured data.