lang-uk/recruitment-dataset-candidate-profiles-english huggingface dataset:
Position: Data Engineer
Category: Data Engineer
Experience: 8 years | English: upper


Bi Developer
VisiQuate
2020 Aug - Till present

Solve business data requests via Microstrategy, SnowFlake, AWS, Azzure and Microsoft Tech stack.

Bi Developer
MedeAnalytics
2017 Dec - 2020 Aug

Participate as BI in cross functional team Productivity Analytics project (2019 till now)

The goal is to build an automated, role based measurement module into Patient Access Information system to measure 100% of role-required employee activity (in real-time) and critical points of employee revenue cycle impact (over the longer term)

• Make different POCs by using elk-stack, kafka+vertica to obtain the right approach for the flexible and scalable product solution 
• Identify data sources are required for different measures (WEB - User input data, 835 - Claims/Denials/Adjustments, HL7 - Patient registration information e.t.c.)
• Solve integration tasks between different systems to align data formats to match records.
• Design data patterns to export from external system and inject data into data warehouse (Spark- HDFS - Vertica).
• Build data flow for real-time data reports and set up ETL for long-term(historical) data points.
• Optimize queries to get the best performance for real-time reports.
• Create customer faced data reports (Mondrian + DVT)

Play BI role in Cost of Operations project (2017 till now)

• Develop 4 products aimed at efficient care delivery: Service Line Analytics, Labor Productivity, Supply Chain and Throughput (Emergency Department & Surgical Service) Claims/Denials/Adjustments, HL7 - Patient registration information e.t.c.)
• Design and build integrated parts to meet criteria of “Enterprise Analytics” strategy. Used Vertica,Sql Server and Mondrian as primary stack.
• Craft different type of reports in SSRS and in Web Enterprise Platform
• Build data flow for real-time data reports and set up ETL for long-term(historical) data points.
• Help to implement products for the clients and support them
• Full filled Scrum Master during her maternity leave. Handled multiple meetings, backlog grooming, inspected velocity and burndown line, added stories and checked their progress during sprints, helped to get fast answers for blocked stories.


e.t.c.
Position: Data Engineer
Category: Data Engineer
Experience: 3 years | English: upper


BI Engineer / Data Engineer
Jul 2022 - Present

Responsibilities:
- Aggregating data from the different data sources
- Ensuring correctness of data in the data warehouse
- Creating dashboards in Logi Analytics
- Developing an additional application 
- Writing documentation

Achievements:
- Developed tools for easier and faster reporting deployment
- Reduced inconsistencies in the database
- Build a reporting tool that provides brief information about data matching
- Wrote production-ready CI/CD scripts


Data analyst / Data Engineer
Oct 2020 - Jul 2022

Responsibilities:
- Aggregating data from the different data sources
- Developing reliable data source based on BigQuery
- Creating dashboards in Tableau
- Ad hoc reporting
- Developing an analytical framework for using within a team
- Writing documentation

Achievements:
- Wrote framework for connecting to multiple sources
- Initiated and ensured the transition from cron to another automation system that allows you to build pipelines, parallel processes, dependencies, etc
- Initiated the transition to BigQuery as the only data warehouse with testing of tables and data integrity. Now we use only it when building reports
- Redesigned many dashboards, both visually and conceptually, and held clarifying meetings with customers.
- Initiated and implemented the transition from periodical reports in Excel to dashboards in Tableau
- Unified the naming of metrics, and documented them in the knowledge base

Junior data analyst
Dec 2019 – Sep 2021

Achievements:
- Modified existing SQL queries to optimize efficiency and decreased execution time by up to 50%
- Created database structure for the client
- Wrote different macros on VBA for weekly reports


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Skills
Databases
- Familiar with: MySQL, PostgreSQL, ClickHouse, MongoDB, MS SQL, BigQuery
- Experience in optimization and performance tuning

Programming
- Applied experience in Python
- Experience in designing, and developing data pipelines
- Experience operating with distributed systems
- Experience with data modeling, data warehousing
- Knowledge of REST/GraphQL APIs
- Experience with Git(GitHub, GitLab), CI/CD, Docker, dbt
- Orchestration tools: Airflow, Argo Workflow

Analytics
- Developed analytics for different business needs
- Automate periodical reporting
- BI: Tableau, DataStudio
Position: Data Engineer
Category: Data Engineer
Experience: 1.5 years | English: intermediate


Big Data Engineer
Developing Python applications for integrating, transforming, and consolidating data from various
structured and unstructured data systems into a structure that is suitable for building analytics solutions.
Researching new methods of obtaining valuable data and improving its quality.
Technologies & Tools
Python, Spark, Spark Streaming, Databricks, Delta Lake, Delta Live Tables, Kafka, Azure, SQL, Debezium,
Docker, Git, Linux, Scrum, Jira.

Back End Developer 
Developing back-end of web applications
Technologies & Tools
Python, Django, Django REST framework, React, JavaScript, HTML, CSS, Git, Docker
Position: Data Engineer
Category: Data Science
Experience: 6 years | English: upper


Big Data Software Engineer
Responsibilities:
· creating views, developing ETL scripts in Teradata;
· developing and supporting NRT DAGs using Apache Airflow & Python;
· collaborating with Business Analysts and stakeholders on projects requirements;
· consuming data from Kafka topics into Teradata using Apache Spark;
· creating pipelines that output data into AWS S3 buckets for Business Intelligence Engineers;
· implementing scripts for backfilling data into production fact tables;
· on-call activities, documenting solutions for arising issues.

Big Data Software Engineer
Responsibilities:
· creating views and stored procedures in BigQuery and Snowflake;
· working on sharding, partitioning, clustering optimization in BigQuery;
· supporting Data Analysts team (reviewing PRs, creating new sources);
· integrating Salesforce sources with Snowflake DW using Fivetran and Segment;
· creating integrations from AWS S3 to Snowflake using AWS SNS topics and Snowpipes;
· executing performance scripts, parsing raw data, documenting implemented solutions;
· developing and supporting ETL pipelines using Apache Airflow & Python;
· configuring data unload from MongoDB, PostgreSQL, MySQL to GCS and AWS S3.

Data Warehouse & Business Intelligence Engineer
Responsibilities:
· creating views and stored procedures in Oracle;
· developing and supporting Qlik Sense dashboards;
· modelling section access structure for a different level application security;
· developing and supporting NPrinting 17+ reports (PixelPerfect, Excel, HTML);
· collecting and analysis requirements for the projects from customers and end-users;
· creating a three-level architecture for projects in Qlik Sense;
· migrating dashboards from QlikView to Qlik Sense and NPrinting reports from 16 to 17+;
· developing and supporting IBM DataStage ETL processes (from files, databases to Oracle);
· developing and supporting SSIS ETL processes (from Salesforce, Google Analytics to Oracle).

Data Warehouse & Business Intelligence Engineer
Responsibilities:
· creating views and stored procedures in MS SQL Server;
· developing and supporting Qlik Sense dashboards;
· uploading customer sales on a daily or weekly basis;
· administrating a system for training and testing (edX);
· creating advanced SQL queries, producing reports using Qlik Sense;
· generating reports by mail from dbms on a weekly or monthly basis;
· unloading user testing results using MySQL, MongoDB and MS SQL Server.
Position: Data Engineer
Category: Java
Experience: 0.5 years | English: intermediate


Bike Rental Service 
Implemented data pipelines such as:
1) Spark streaming from MinIO into Kafka topic
2) Spark batch pre-processing data for further computation
3) Spark batch processing two datasets from MinIO and Cassandra with further saving to Elastic and visualization in Kibana
4) Kafka alert producer via Kafka Streams API
Additionally, I was responsible for: Spark Stateful Streaming operations; building uber-jars and creating common Utils module using Maven; Airflow with Spark containerization and deployment using custom image.
As a team member, I was involved in writing docker-compose files and entrypoint scripts for setting up the environment, configurating spark to execute multiple jobs in FAIR mode, creating DAG for batch jobs orchestration via airflow and bug-fixing on every development stage as well.
Position: Data Engineer
Category: Scala
Experience: 3 years | English: fluent


Building ETL pipelines using AWS Glue (Spark) in Scala. 
Implementing AWS API Gateway + AWS Lambda based API interface.
Working with AWS Lambda to execute a variety of other tasks, for example email sending, schema validation, workflow configuration backup.
Interested in a switch to Python/PySpark.
Position: Data Engineer
Category: SQL
Experience: 5 years | English: upper

Built data warehouse on Hadoop+Hive from scratch and set up ETL from various datasources
I have done various research projects to improve company performance (Fraud detection, Tracking issues, etc)
- building, tuning and maintaining Data Warehouse
- design, setup and launch ETL processes
- providing complex custom reports for Product Analysts and Product Managers for different projects
- monitoring of data quality
- monitoring business metrics, issues investigation and researching
- experience in processing both structured and unstructured data
Would like to work in a data-driven company with technical challenges that will allow enhancing my professional skills
Position: Data Engineer
Category: Data Engineer
Experience: 0.5 years | English: upper

Graduated with distinction in ML Engineering, Data Engineering, and Web3 intensive training/internship from 10 Academy.
Built an ELT Data Warehouse pipeline for traffic data collected through swarm UAVs.
Helped build an ETL data collection pipeline using Airflow, Spark, and Kafka.
Helped to build an end-to-end MLOps for an A/B ad campaign performance hypothesis test using Machine Learning.
Helped to build a scalable backtesting framework for crypto-trading strategies resulting in 70% profit.
Built a causal model for a client that provides delivery services in Africa.
Position: Data Engineer
Category: SQL
Experience: 5 years | English: upper


Business Intelligence Professional with 4+ years of experience
- Oracle Certified Specialist (OCA-071)
- Oracle Database PL/SQL Developer Certified Professional
- 4 years working within a financial environment
- Expertise in building templates, dashboards and analyzing data using BI Tools (Power BI, Oracle BI, Tableau)
- Expert knowledge of Oracle and Postgre SQL (3+ years) 
- Experience with PL SQL/T-SQL languages
- Statistics and modelling expertise
- English – Upper-intermediate
Position: Data Engineer
Category: Data Engineer
Experience: 7 years | English: fluent

I am Senior Level Data Engineer with about 6 years of experience in the field Business Intelligence. I have huge experience in SQL Database development using mostly TSQL , PL SQL, MySQL and many others; and  ETL work using SSIS and Azure Data Factories mostly;  and Datawarehouse Design , Report writing using different tools like PowerBI and SSRS mostly.
T-SQL is one of my strongest skills. I created several complex and efficient stored procedures, user defined functions, triggers, views, indexes and almost all other database objects. Also, I am strong at SQL performance tuning and troubleshooting.
For Data Engineering and ETL work, I have done development, configuration, and deployment of many SSIS pkgs and Azure Data Factory pipelines in both OLAP and OLTP environment. 
I have also great experience in data modeling for creating ERD models for OLTP systems and Dimensional Models for Datawarehouse.
CLIENT:         DataSite Technology
  ROLE:             SQL BI SSAS, SSRS, SSIS Developer 
  DURATION: June-2017 – May-2019
 
 CLIENT:         Shell
  ROLE:             ETL/MSBI Lead, Architect 
  DURATION: August-2019 – Present
Position: Data Engineer
Category: SQL
Experience: 11 years | English: upper


• Cloud: Azure: Data Factory, Databricks, SQL DB, Synapse, Storage account
• Data analysis: Python (expirienced), R (basic level)
• MS SQL Server (experienced)
• Reporting and dashboards: MS Reporting Services, MS Power BI
• ETL: MS Integration services, Control-M
• Team management: building up and management of a software development team
• Technical design: developing concepts for the implementation of new requirements, defining user stories, prioritizing requirements and maintaining the product backlog, planning of release and responsibility for functionality, usability, performance and quality

Summary

• 8 years of working experience in database development area, more than 10 years in software development area.
• Persistence in achieving goals, team player, good communication skills, high level of adaptability, leadership skills, strong mathematical and analytical skills, high level of responsibility.
Position: Data Engineer
Category: Data Engineer
Experience: 3 years | English: upper


Collected and cleansed large datasets, applying data wrangling techniques to ensure data quality and consistency. Implemented data validation and cleansing processes to identify and rectify anomalies and discrepancies in the data.
Utilized Spark to implement distributed data processing, enabling faster and more efficient analysis of big data. Leveraged Spark's capabilities for parallel processing and in-memory computing to handle large-scale data sets and improve data processing speed.
Developed robust ETL pipelines using Airflow, orchestrating the end-to-end data flow from various sources to the target database. Created and maintained DAGs (Directed Acyclic Graphs) to schedule and monitor data extraction, transformation, and loading tasks.
Collaborated closely with project managers and analysts to understand their data requirements and deliver optimized data pipelines that supported their KPI tracking needs. Translated business requirements into technical specifications, ensuring the data pipelines met the desired outcomes.
Actively participated in project documentation design and maintenance, ensuring that all processes and procedures were well-documented and easily accessible to team members. Created comprehensive documentation for data pipelines, including data flow diagrams, data mappings, and transformation rules.
Worked with a range of tools and technologies including Python, ETL, PySpark, Postgres, Redshift, Alembic, Airflow, AWS Services, Jenkins, and BitBucket. Leveraged these technologies to design, develop, and deploy data solutions that met business needs.
Position: Data Engineer
Category: Python
Experience: 0.5 years | English: fluent

Commercial experience is absent, but I've completed the DataRoot Labs Data Science course, and several other courses about Machine Learning (by Michigan university on Coursera) and Deep Learning (by Andrew Ng on Coursera). 
Currently working as a Junior Game Tester
Competed in several Kaggle Competitions, created Exploratory Analysis Jupyter Notebooks, where I looked at apartments dataset, which I webscrapped myself, and a restaurants of Kyiv according to TripAdvisor data set, which I also scrapped myself.
Position: Data Engineer
Category: Data Science
Experience: 7 years | English: upper


Completed several SAP HANA DWH BI projects. 

Responsibilities: Data modeling using Dimension Views, Star Joins, Calculation, and Custom/Scripted Views. Modeling security models in HANA specific to schemas, packages, and analytical privileges 
Developing Tables, Procedures, Table Functions, XSJS/XS OData API services Performance Tuning and Query Optimization
Developing Data Extraction Transfer Loading (ETL) processes using SAP Data Services and Python.

The reporting and Business Intelligence system of Telecommunication Management that includes Ad-Hoc Analytics, On-Demand Data Exports, Interactive Dashboards.

Responsibilities: Designing, developing, and maintaining a reporting environment. Developing PL/SQL Stored Procedures, Functions, Packages to implement Business Rules, preparing ad-hoc SQL reports. Designing, developing Universes in Business Objects Designer for generating the marketing reports
Optimizing the universe and SQL tuning to increase the query performance.
Highly skilled data engineer with over 9 years of experience in business intelligence, data management, and data engineering. Proficient in Python and experience in developing ETL pipelines, data modeling, and building data systems using Hadoop Stack and various databases such as Vertica, MySQL, and SingleStore. Strong background in SAP HANA Financial Reporting and Oracle database. Looking to further develop skills in data system architecture
Position: Data Engineer
Category: Data Engineer
Experience: 0 years | English: intermediate


Configured Amazon Kinesis Data Firehose to extract streaming data from the source
and then upload it to S3. Created delivery stream in which configured partition of
extracted data.
Created and deployed a CloudFormation template for an S3 bucket in which
configured the name of the bucket and access rights.
Scripting: Written python script for reading the parquet data from the corresponding
S3 location using the boto3 client for S3. Extracted partition attribute value
separately from the respective partition prefix. Created class that corresponds to the
events structure and mapped the events to the class instance. Collected instances in
the list and output to stdout.
Created and configured Glue Job with the Spark script editor, which uses the
concatenate and aggregate functions, added a new column to the created dataframe,
which is calculated ecpm according to a formula in which contained data from other
columns. Uploaded data to S3 storage.
Created dashboard in Grafana in which added 4 panels in which displayed
information by device for some metrics. Performed query using the Athena query
string to query data in AWS Glue data table created before.
Position: Data Engineer
Category: Data Engineer
Experience: 4 years | English: fluent


Create and build data warehouse platform from zero for a banking company. which includes optimizing and creating ETL processes using Python, Pyspark. migrate, modify a data with appropiate requirements and store them on HDFS platform for further usage.
as well as developing an application(angular/django) which orchestrates these processes and makes it automated.
Position: Data Engineer
Category: Data Science
Experience: 0.5 years | English: fluent


Created a fully functional search engine capable of answering user queries. Developed a highly-scalable distributed system that uses Elasticsearch as a full text search engine and asynchronous Python backend
 Built a pipeline of automated integration and cloud deployment of Docker images with Ansible scripts
 Developed parallel web crawler that maximizes the use of machine's resources for better efficiency
 Applied language detection model on parsed web pages based on N-gram analysis
 Implemented own power method-based fast PageRank algorithm for advanced search results ranking
Performed algorithm benchmarking, ranking quality tests, and written a research on this topic
 Configured load balancing using nginx, performed load and stress testing
 Gained experience with system security hardening and working in Linux environment
Position: Data Engineer
Category: SQL
Experience: 2 years | English: intermediate

We were doing data migration from Hadoop to Snowflake 
I tasted pipeline. Created script and generate a report for Business 
Generated instructions for support team. I used to "Confluence" and "Jira"
I spook with Develop team and I had talked about issue in the pipeline.
•	Create logical, create mapping and SQL code for Developer team.
•	Testing new logical, new table
•	Data quality
•	Communicate with business and find ways for resolving issue 
•	We use: SQL Oracle, Oracle data integration, Git, Jira, Confluence, Excel(VLOOKUP), VMware
•	Creating views, tables, procedure , function, testing procedure
•	  Slack,  Monday, Webex.
•	Calculation events. 
•	Calculation Cybersport events.
•	Creating  DB, sql Server, Snowflake.
•	Design DB.
•	Creating views and stored procedure.
Position: Data Engineer
Category: Data Engineer
Experience: 2 years | English: fluent


Creating data pipelines extracting from API data or other databases like Oracle. Data sources: FB, FBAds, Google analytics, Instagram and couple of internal databases regarding some technical data. Currently implementing Unity Catalog in Databricks and evaluating new features like liquid clustering.
Position: Data Engineer
Category: Data Engineer
Experience: 4 years | English: upper

Creating own variation of Airflow(tool for orchestration of tasks with workers and metadata). Creating hyperparametrized ELT pipelines, which takes data from 1000 of different data sources and calculating marketing and product metrics for analytics. Creating a DWH with kimball metodology.
Creating realtime synchronization system of SQL(Postgres) and NoSQL(ArangoDB,ElasticSearch) DB's with Kafka,Debezium and Python.Developing Big Data Pipelines with Talend,Airflow and Python. Deploying projects with Docker and Kuberneties.
Having good experience with new technologies.
Position: Data Engineer
Category: SQL
Experience: 4 years | English: intermediate

Complete integration between Google Big Query and CRM
+ Creation and maintaining data-lake for all departments in company
+ Transfer data from different sources to Data Warehouse
+ Writing ETL scripts
+ Routine automation
+ Data exchange between CRM and Data Warehouse with hand-written scripts and Google Cloud Platform tools
+ Preparing tools for data collection on the website
+ Creating ad-hoc and regular reports
+ Resources monitoring
+ Preparing regular notifications and alerts
Office at Dnipro city
Position: Data Engineer
Category: Data Engineer
Experience: 1 years | English: upper


Currently, I am involved in an internal project focused on developing a resources accounting platform. Within this project, I hold the positions of Data Engineer and Data Analyst. My responsibilities primarily involve integrating monthly data into MS SQL and creating Power BI reports. This includes extracting raw data from our OLTP system, performing data cleaning, creating data models, and finally visualizing the data. To accomplish these tasks, I utilize various technologies such as Power BI Dataflow, M query, DAX, and T-SQL.
Position: Data Engineer
Category: Data Engineer
Experience: 1 years | English: fluent


Currently I work as Data Entry Specialist at GeeksForLess Company.

I studied an online course "QA Manual" at Beetroot Academy(Sep 2022-Nov 2022). Also, I passed an online QA marathon on GoIT course in November.

Previously, I worked as Customer Support Representative(USA) and English teacher.
Interesting projects and communication with the team.
Position: Data Engineer
Category: Data Engineer
Experience: 5 years | English: intermediate


Currently I work at the International Information Technology University as senior lecturer. Besides, for the last 3 years I worked in the company ALLDATA as a data engineer. Our team tasks were collecting a data and preparing it to front-end and back-end teams with the help of ETL tools, writing Python scripts and SQL queries, automatizations on Apache Airflow with Celery executor, administrating a Data Warehouse(Postgres). Also, I have a little experience in the field Cloud Technologies