lang-uk/recruitment-dataset-candidate-profiles-english huggingface dataset:
Position: Data Engineer, Data Scientist
Category: Data Engineer
Experience: 4 years | English: fluent

- Led and developed numerous BI projects that were used to find anomalies, to optimize data warehouse / ETL processes, logistics and resource management for DAX companies
- Saved costs and operational overhead by supporting migration from Power BI, Tableau, Cognos and Superset to Qlik Sense
- Received positive feedback and 5* reviews from the happy clients on Clutch
- Led several business development initiatives to help the company expand their client portfolio
PROFILE:
I have 4+ years of building Data Analytics for different business departments of the DAX companies as well as 5 years of working with complex data in Academia (Postdoc and PhD). I am interested in building Cloud and Big Data Analytics solutions

SKILLS:
My expertise includes identification of requirements, architecture, data modelling, DWH, ETL and visualization from the concept phase to the production. Qlik Sense, SQL, AWS,
GCP (Data Analytics stack), Dataiku
I am looking for remote / part time projects in Data Engineering with a possibility to develop my skills futher. Industry is not very important, however Pharma/Biotech would be preferable. My core competence is Qlik Sense (ETL, DWH, data modelling, data visualization), however I am searching for projects, where i would be able to improve my skills in AWS / GCP / ML
Position: Data Engineer && Data Scientist (Middle)
Category: Data Science
Experience: 2 years | English: upper

More on LinkedIn
- Spark & PySpark  / DataBrikcs / SQL / Python / PyTorch / MxNet
-  Data preparation, manipulation, transformation, visualization and interpretation 
- ETL processes, experience in Data Warehouses, Data Lakes (Azure)
- ML solution for data anomaly detection, predictions, time series, classification, regression, market segmentation etc. 

Certifications: 
*Databricks Certified Associate Developer for Apache Spark 3.0 (Python) 
*Harvard CS50’s Introduction to Artificial Intelligence with Python
*Amazon training and certification 2020
*Cisco Networking Academy® self-paced course

Primary education:
*Finance & Credit
*MBA
Small projects not mote than 20 hours per week!
Position: Data Engineer \ DBA \ Data Analyst \ BI
Category: Data Engineer
Experience: 6 years | English: fluent

I take pride in building reliable data pipelines "from scratch" for several international companies.
Self-educated in Python & Big Data, so whenever I join a new project - I can learn its new technologies and adapt all by myself, no baby-sitting required))
Skills: Data Processing and Analytics (10+ years)
SQL (SQL Server, MySQL) – 4 years
AWS (S3, Athena, Redshift, Databricks) – 2 years
ETL pipelines (SSIS, Databricks, PySpark, Airflow) – 2 years
BI dashboards (Looker, PowerBI, Tableau) – 3 years
DBA (SQL Server) – 1 year
Foglight, Powershell, Google Colab, Jira/Confluence, Git, Jenkins.
NLP and Text Mining (spaCy, gensim), web parsing (requests, selenium).

Collaborative, flexible, passionate to evolve, face new territories and challenging tasks.

Some of my projects: 
- top-10 computer parts vendor
- top-10 Online Video Platform
- major Forex broker with worldwide coverage.

I prefer projects which do not just utilize my superpowers, but also allow me to master new ones and grow as professional. 

My passions: fine-tuning convoluted systems, finding bugs in them, polishing them to perfection. 
Studying data to discover hidden patterns behind it, improve understanding of real processes and people, and ultimately provide valuable insights which can lead to tangible results.
Challenging data-related tasks; 
Opportunities & motivation for self-development and learning new cutting-edge big data technologies;
Chance to extract valuable insights from data, which will influence decision-making;
Efficient & fast communication with the team, ability to ask many questions in order to get deep understanding of the product and business.
Position: Data Engineer / DBA/ DB developer
Category: SQL
Experience: 11 years | English: upper


Database developer with 10+ years of hands-on experience in DBMS, including high-volume DB. 
Strong knowledge of data manipulation and programming, creating, maintaining and optimizing 
database elements, database design, performance tuning, backup/restore technologies, ETL, 
DWH, requirement analysis

Additional experience:
 - Azure Cloud services
- Python (Pyspark)


Latest project:
July 2019 – April 2022
Position:
Senior Database Developer
Development of a market analytics platform 
Responsibilities:
• Designing and developing technical solutions using various MS SQL concepts and objects 
such as stored procedures, views, functions, triggers, temporal tables, in-memory OLTP, 
partitioning, SQL jobs, SSIS packages, linked servers, replications, log shipping 
• Preparing SQL queries, reports, and data extracts in an ad-hoc and regular manner 
• Performing and managing daily database maintenance, index/backups strategy, monitoring 
and performance tuning tasks, optimization and automation of existing procedures and 
processes 
• Moving database related project environment from on-premises to Azure virtual machines, 
implementing Azure Blob Storage solutions in accordance with the project needs 
• Developing ETL solution based on Databricks, PySpark, Azure Data Lake
Technologies and tools 
• MS SQL, SSIS, Azure, Databricks, PySpark

I'm interested in data engineering , SQL/DB development

Thanks!
Position: Data Engineer/ DWH Developer
Category: Data Engineer
Experience: 4 years | English: fluent

Developed and built an internal cloud analytics system from scratch (stack: Apache Kafka - Apache Nifi- dbt -
BigQuery - PowerBI)
- Deployed a secured instance of Apache Nifi on Google Compute Engine vm
- Development of various dashboards in Power BI 
- Modeled DWH using dbt (Kimball approach)
- Connected to various third-party APIs to collect and enrich the data
- Generating and testing various hypotheses for customer acquisition and retention
- Assisting management with everything that concerns data
- Automated report email send out with Google App Script
Google Cloud Certified Professional Data Engineer (02.01.2023) 

Below is the list of tools and technologies I used for various purposes. 


Languages: Python, SQL, DAX (Power BI) & M (Power Query)

Technologies: Apache Nifi, Kafka, Airflow, Apache Beam, dbt, GCP (BigQuery, Compute Engine, Cloud Functions, Dataflow etc.), Git, Docker

BI: Power BI
What I am interested in is working in a company that understands the value of modern cloud analytics and either already has implemented such a system or strives to do so. Ideally, I would like to keep working in GCP as I am quite well-versed in the system. However, if your cloud platform is AWS, I am okay with that - just keep in mind that my experience in this system is not as expansive as in GCP.
Position: Data engineer (DWH, GCP, Airflow, CH)
Category: Data Engineer
Experience: 4 years | English: upper

I have won hackathons organized by prominent companies like banks and Microsoft, where I developed a prototype of a device that enables visually impaired individuals to play sports. My innovative solutions and dedication to problem-solving helped me secure first place in these competitions.

As a programming instructor at a coding school, I created a course that helped train and prepare aspiring developers for a career in IT. Thanks to my course, 10 students were able to secure roles as backend and frontend developers, analysts, and UX designers, making a meaningful impact in their careers and the technology industry.
As a data engineer with 3+ years of experience, I specialize in designing, building, and maintaining data pipelines and infrastructure. I have expertise in various data warehousing tools, including ETL processes, data modeling, and data integration. I aim to optimize data processing and flow to ensure accurate, timely, and secure data delivery, enabling data-driven decision-making.


Projects in SAAS-based company 

• Engineered and supported 50+ completely automated ETL jobs using Airflow, Python, and SQL (Clickhouse, MySQL, Postgres, ElasticSearch).
• Redesigned data pipelines that helped to optimize execution time by 50%
• Provided sales and marketing teams with required data for different campaigns. The churn rate decreased to
12%
• Led documentation of processes and data solutions

Projects in the outsourcing agency (the largest partner of Google in APAC region) 

• Built a series of Marketing Dashboards for Korean automobile manufacturers using Data Studio/Looker.
• Implemented statistical analysis of the website events to identify key business actions that drive the business using GCP (BigQuery mostly), GMP (CM360, DV360, SA360, Google Analytics (UA + GA4), and GTM)
• Assisted in implementing a machine learning model to identify users with a higher probability of conversion.

Projects in the telecom company

• Enriched DWH with 100k houses data on competitors’ technical capabilities by integrating a self-designed scalable web crawler.
• Collaborated with the marketing and data team to satisfy analytical needs by building both large systematic reports and small custom pieces.
• Developed and supported data infrastructure and ETL processes
I prefer not to work with companies in the gambling, betting, alcohol, and tobacco industries due to personal values and beliefs.
Position: data engineer/ etl developer
Category: SQL
Experience: 10 years | English: intermediate


Experience
•	5+ years of outsource experience in software development (including Regulatory Reporting Projects and Reference Data Services)
	10+ years experience in the IT industry
•	Maintenance  and implementation of ETL processes (data extraction, transformation, loading, cleaning, validation) .
•	Development with experience and knowledge in all stages of project life cycle.
•	Experience in Database Architecture and Data Modelling
EMPLOYMENT

Oracle/ETL Developer, Jun 2013 - currently Luxoft, Ukraine.
 
	Projects: Client onboarding, Regulatory and Control, Reporting system
Description: The project mission is creation of a unified system for client onboarding.Migration from legacy systems.Loading regulatory client information. Creation of a reporting system.
Duties:
o	Development of the real-time and batch ETL processes according to the specifications:
 		on Informatica side (mappings/workflows);
 		on database side (packages/procedures/functions etc.);
o	Integration with external system using Informatica ,(external source –Oracle DB, SQL Server DB, Salesforce, SOAP and REST WS, files in different formats;
o	Data modeling including the design and development of Oracle and ETL processes;
o	Non-PROD environments testing support;
o	Performance tuning;
o	Incident and defect analysis and fixing;
o	Environments setup and synchronization (sanity and smoke checks);
o	PROD rollout preparation and  support;
o	Creation of the Control-M jobs/packages for workflow scheduling;
o	Communication with local and remote/distributed teams (UK, US, India).


Oracle Developer, Oct 2012 - Jun 2013 Miratech
Ukraine

	Duties:
o	Design, develop, maintain billing system ;
o	Create a logical database structure, scripts, queries, packages, views, jobs,
Tuning of SQL queries
o	ETL development using PL/SQL;
o	Communication with technical and analytical specialists from customer side;
o	Ad-hoc reporting;
o	Technical support of L3 and L2 services, technical customer support


   Oracle Developer, Jul 2008 - Sep 2012  Internal Revenue Service

	Duties:
o	developing of applications framework for Tax Accounting and Reporting Department (Visual FoxPro, Oracle);
o	developing a server-side software for data aggregation and data selection (PHP, Oracle);
o	Tax system support.
Position: Data engineer / ETL developer
Category: Data Science
Experience: 7 years | English: upper


Core Technologies and Tools:
SQL, PL\SQL, Oracle
Python 3 Core, Java Core, OOP
DWH, ETL, Informatica PowerCenter
JMS, Kafka, RabbitMQ, XML, JSON
Jenkins, TeamCity
SVN; GIT 

Knowledge and Skills:
Oracle – knowledge of Memory Structure; Database objects; Partitioning; Materialized view; Locking; Transactions.
Performance tuning - experience in processing of big data; Execution plans; Tables, Indexes; Join methods; Hints; Statistics gathering, AWR reports.
SQL – Writing queries of varying complexity; Data manipulation; Analytical and Grouping functions, Regular expressions, Hierarchical queries.
PL\SQL – Procedures, Functions and Packages; Collections and records; Bulk loads; Cursors; Exception handlers; Dynamic SQL.
Python scripting – Python 3 Core
Java – Java Core, OOP principals
Informatica – Mapping and Workflow development and support
JMS, Kafka, RabbitMQ, XML, JSON
GIT, SVN – Version Control Systems
JIRA, Confluence – Bug-tracking systems
Position: Data Engineer / ETL / DWH
Category: SQL
Experience: 5 years | English: upper

- resolving migration issues
- performance enhancement
Experience: Database Development

Area: DWH, ETL, Cloud

Tools/Technologies: SQL, Talend, Python, AWS Data, Azure Data, Snowflake

Projects: 
- on-premise -> cloud data migration
- migration between different DBMS's
- data migration
- DWH design / development / management
Position: Data Engineer (GIS)
Category: Data Engineer
Experience: 9 years | English: intermediate

Professional Data Engineer and GIS Analyst with nearly ten years of experience with ArcGIS software for developing GIS databases as well as Editor data creation / editing tools and snapping tolerances. Demonstrated skills in customer interaction marketing and basic sales work. Continuously looks at ways to add value to take the initiative in improving processes and identifying business opportunities.
Data engineering, Data analytics, GIS, Implementation of geographic information systems, Business analytics, Spatial analysis, Remote sensing

-Python
-SQL
-Git
-GIS API
- structure data and algorithm
-gis (arcpy)
-math ( numpy, pandas, matplotlib)
-Google API
-MapBOX
-Google Colab
- ETL
Data engineering. GIS. Remote sensing.
Position: Data Engineering (BI/MSSQL/ ETL developer)
Category: SQL
Experience: 11 years | English: intermediate

Reporting automation
•‎ Develop and maintenance of analytical systems (OLAP-cubes) MS SQL Server Analysis Services (SSAS). 
•‎ Support the establishment of procedures and MS SQL Server Integration Services (SSIS). 
•‎ Develop reports in MS SQL Server Reporting Services (SSRS) and PowerBI. 
•‎ Develop and maintenance of DWH. 
• Development and maintenance using the C#, PowerShell, PowerQuery M, PowerPivot, DAX, Jira, T-SQL, CosmosDB, MS Synapse
•‎ Developing, publishing, and scheduling Power BI Dashboards/Reports as per the business requirements including drill through, drill down to SSRS reports;
•‎ Advanced Hands-on use of Power BI & Power BI Tools & Power BI Premium
•‎ Develop visual reports, dashboards, and KPI scorecards using Power BI desktop
• Connect to data sources, importing data, and transforming data for Business Intelligence
• Create and maintain SQL scripts and objects (functions, stored procedures, views, etc.)
• Use embedded analytics like Power BI Service/Embedded
• Integrate Power BI reports into other applications
• Work with Power BI Client API and Power BI Rest API
• Capable of implementing row-level security on data along with an understanding of
application security layer models in Power BI
• ETL (Extract, transform, load)
• Design and implement the Data Flows and Data Warehousing
Development of reporting in SSRS and POWER BI. Part-time or hourly payment
Position: Data Engineering, Developer
Category: Python
Experience: 0 years | English: intermediate

Confidently completed courses at the IT school Hillel on the course "Basic Python".
Successfully passed the training course from Nix Solutions "Python education". I've worked with building different database schemas, fill them with data from several sources via PostgreSQL. Also, I touched Apache Airflow and created several ETL services, worked with libraries such as pandas, PySpark and wrote unit tests via Pytest. Learned many tools like Git, Docker and etc.
On the course were many challenging tasks that required to find interesting approaches for them.
The last experience was the tiny project of downloading raw information from the website. Parse date once, upload to the S3 bucket and use Airflow to schedule and download new information that appears during the day. After that, the processed information is uploaded to the database (PostgreSQL) and also uploaded every day according to the schedule. Transformed to the desired format and combined with other data according to certain criteria.
I have expireince in Big Data, built ETL and want continue work with it, but this pleasure teach and use new tools.
Position: Data Engineering Intern
Category: Data Engineer
Experience: 1 years | English: fluent


Built ETL that ingested data from a website to Postgres database.
Designed and implemented data pipeline to process data from multiple sources using SQL, Prefect, Terraform and GCP.
used docker to dockerize and containerize python script for data ingestion.
Created a Flask API.
Data Engineering Intern motivated by data and results, ready to join a team to build a data stack from scratch.
Position: Data Engineer Intern
Category: Data Engineer
Experience: 0 years | English: intermediate

Currently I'm looking for internship of the Business Intelligence developer role. I'm in progress of self-learning SQL and Azure Data services
During last five years i was working as security systems installation and configuration engineer in Euroinstal company (Warsaw, Poland). Company is specializing on video monitoring, access control and fire safety.
Position: Data Engineer, Java Developer, Cloud Engineer, Cloud Architect
Category: Data Engineer
Experience: 11 years | English: fluent

• Certified AWS Machine Learning Specialist (Amazon, Validation Number: YJJTVLDKHM111B5P) - Exam passed successfully
  • Certified AWS Solution Architect PROFESSIONAL (Amazon, Validation Number: Q5YFD7EC3FQQQ23Y) - Exam passed successfully
  • Certified AWS DevOps Engineer PROFESSIONAL (Amazon, Validation Number: TMQ7ZVW13NB41ZW6) - Exam passed successfully
  • Certified AWS Security Specialist (Amazon, Validation Number: EP84L54KGNB41VKF) 
  • Certified Azure Solution Architect Expert (PROFESSIONAL) (Microsoft, Certification number: H218-2646) - Exam passed successfully
  • Certified Google Cloud Architect PROFESSIONAL (Google, Certification ID: 6zTqfr) - Exam passed successfully
  • Certified AWS Developer (Amazon, Validation Number: 9T4NM16CBBQEQT9C) - Exam passed successfully
  • Certified AWS Architect (Amazon, Validation Number: 6GSY8YS1DMQQQG9R) - Exam passed successfully
  • Certified Kafka Developer (Confluent, 12263104) - Exam passed successfully
  • Certified Spark & Hadoop Developer (Cloudera, License: 100-017-901) - Exam passed successfully
  • Certified Cassandra Developer (DataStax, Certificate ID: 16f135c3-a433-4363-8518-de1f4a18c070) - Exam passed successfully
  • Certified Hadoop Administrator (Cloudera, License: 100-017-901) - Exam passed successfully
  • Certified HBase Developer (MapR, License number: ipupzqv6nzj6) - Exam passed successfully
  • Certified MongoDB DBA (MongoDB, Certification Number: 565804091) - Exam passed successfully
  • Certified MongoDB Developer (MongoDB, Certification Number: 996745314) - Exam passed successfully
  • Certified Neo4j Professional (Neo4j, License number:  16681227)
  • 5 years’ commercial experience in BigData
  • 6 years’ commercial experience in AWS
  • 6 years’ commercial experience in Scala
  • 12 years’ commercial experience in Java (including concurrency and multithreading), Python, Ruby 
  • 7 years’ commercial experience in e-commerce
  • 2 years’ commercial experience in C++
-   17 years’ commercial experience in software development
-   several business domains
-   hands-on architect but consider the following roles: Architect | Developer | Engineer | DevOps
- 	focused on cutting-edge technologies
- 	experience confirmed by certificates issued by Amazon, Google, Microsoft, Cloudera, Confluent, MapR
Fully remote projects. FinTech is preferable but any business domains are considered.
Position: Data Engineer, Lead, Architect
Category: Data Engineer
Experience: 11 years | English: upper

- Implemented and partially designed a few complex long-term big data projects from zero to release (i.e., lambda architecture in AWS for near real-time brokers market analytics, and modern Lakehouse/Warehouse for telecom ML/BI in Azure)

- Did architecture discovery, assessment, MVP in role of Big Data Architect / Consultant. As part of this did significant impact on projects architecture and success.

- Tried myself through all end-2-end project lyfecycle: presales, discovery/assessment, team & processes setup, implementation, ongoing support & tunning. Achieved some kind of balance in technologies & approaches between depth (long-term projects) and width (short term projects).
Many Big Data projects, in engineering and architecture roles, everything in CV. 

Among them complex big data projects (lakes, dwh, batch, streaming, migration) from ground up, requirements collection, design, architecture discovery/assessment, implementation, team leadership, etc.
- Legacy systems where all decisions made before me
- Purely managerial roles, where despite Lead/Architect title 80%+ of time is spent on managing others and their expectations