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Director Expertise at Adastra (Global Delivery, EMEA) | Kaggle Machine Learning Competitions Expert
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University of Veliko Turnovo "St. Cyril and Methodius"
Bachelor of Economic management, Economic management, Econometrics, Quantitative methods in economics, Statistics
N/A – Present
College of Management, Trade and Marketing - Sofia
Bachelor of Marketing, Marketing
N/A – Present
Adastra
Director of Expertise, Global Delivery EMEA
November 1, 2023 – Present
Sofia City, Bulgaria · Hybrid
Adastra
Data Management and Data Science Practice Lead
October 1, 2022 – November 1, 2023
Sofia City, Bulgaria · Hybrid
Tipico
Data Scientist
December 1, 2019 – October 1, 2022
Malta
Mr Green Online Gaming
Senior Data Engineer
May 1, 2018 – December 1, 2019
Malta
Cherry AB (publ)
Machine Learning Engineer / Senior Data Engineer
January 1, 2016 – May 1, 2018
Malta
Adastra
Data Warehouse Consultant / Data Quality, ETL and BI (Business Intelligence) Lead/Developer
February 1, 2011 – January 1, 2016
Toronto, Canada Area
Overgas Inc
Chief Analyst “Clients Database” / Statistician
April 1, 2008 – February 1, 2011
Kaggle's Digit Recognizer machine learning competition
May 1, 2017 – July 1, 2017
Sophisticated machine learning model created to recognize hand-written digits: - made up of 20 Deep Convolutional Neural Networks - supported by 10 Variational Deep Learning Autoencoders - relying not just on "previous experience" (training data) - but also on its ability to "imagine" new variants of the symbols - and use them to extend its capability. - evolved and finally stacked with the help of Genetic Algorithms Model reached perfect accuracy (100%) on Kaggle's Digit Recognizer competition (check leaderboard - competition is still ongoing) - and this secured my place amongst the top 20 teams (out of 1800+ teams! on this event). ENVIRONMENT: Python: Keras (TensorFlow), Pandas, NumPy, scikit-learn, inspyred
Vendor/Product MDM POC project, Loblaw Companies Limited
April 1, 2015 – May 1, 2015
Delivered Proof Of Concept DQ/MDM solution, 5 source systems Worked as project lead with team of developers and analysts Provided full stream architecture for MDM implementation Architected Data Model for MDM solution Gathered requirements for Parsing, Cleansing, Matching, Merging and Reporting Developed Ataccama DQC ETL/DQ code - Acquisition, Automatic cleansing, Matching, Merging (Golden records creation)) Performed analysis on the results, decided on the final Reporting/Visualization solution look and content (MicroStrategy) Created final deliverables (presentation, report of findings) and presented to the client ENVIRONMENT: Ataccama DQC v.9, Oracle 11g, Teradata 13
Enterprise Reference Data Management (RDM) project, Rogers Communications
December 1, 2014 – March 1, 2015
Delivered large scale end-to-end RDM solution, synchronization with multiple source systems Worked as dev lead with team of developers Provided full stream architecture for RDM implementation Revised requirements regarding Data Elements/Relationships/Hierarchies, Cleansing and Validation, Data Acquisition and Synchronization, Business Processes/Workflows, Schedulers and Notifications, Users/Authentication/Authorization. Designed, prototyped and developed: RDM Repository Tables, Views, Relationships/Hierarchies, Cleansing and Validation routines, Business Workflows, Data Acquisition and Synchronization jobs, Schedulers and Notifications ENVIRONMENT: Ataccama RDM v.9, Ataccama DQC v.9, Oracle 11g, PowerShell, Python 2.7
BMO (Bank of Montreal), Enterprise MDM (Master Data Management) Project, Project Lead via Adastra
August 1, 2014 – Present
Delivered large scale end-to-end DQ/MDM solution, 8 source systems Worked as project lead with team of developers and analysts Provided full stream architecture for MDM implementation Architected Data Model for MDM solution Gathered requirements for Data Quality Analysis, Data Elements, Parsing, Cleansing, Matching, Merging, DQ Monitoring, DQ Dashboards and Reports Designed and prototyped Data Quality Processes Developed Ataccama DQC ETL/DQ code - Acquisition, Automatic cleansing, Data Quality Metrics Measurement, Matching, Merging (Golden records creation)) and Reporting Developed Ataccama DQD code - DQ Dashboards and scorecards Orchestration/scheduling process designed and developed ENVIRONMENT: Ataccama DQC v.8, Ataccama DQD v.8, Ataccama DQIT v.8, MS SQL 2008 , 2012, PowerShell
MPAC (Municipal Property Assessment Corporation), DQ Assessment, statistical analysis, DQ Lead via Adastra
July 1, 2014 – August 1, 2014
Led a team of developers Gathered and documented the data definition (metadata) Defined data rules, valid ranges and exceptions Data transformed, profiled and analyzed Implemented Ataccama plans to represent and validate the business rules Flagged DQ issues and prepared detailed DQ report Performed descriptive statistical analysis on massive datasets using R (programming language) – distributions, correlations etc. Conclusions and findings validated, described and presented ENVIRONMENT: R, Ataccama DQC v.8, PostgreSQL 9, PowerShell
Walmart Canada Bank, ETL solution, ETL Lead via Adastra
January 1, 2014 – May 1, 2014
Led a team of developers (managed, organized and distributed tasks) Mentored junior developers Created design patterns and development standards Performed Source System Analysis - Data profiling and Assessment Designed and prototyped solution Created Detail Design Specifications Performed development of Ataccama based ETL Solution: plans (code) to extract data, map to target model, perform Surrogate Key Generation, apply SCD2/SCD1 algorithms, merge data to the Integration layer, populate system control and error tables etc. Designed and built the orchestration of the system (Bash/Perl scripts, PLSQL procedures, workflows) - incorporated process and data error handling, restartability, parallelism control, notifications, archiving and other mechanisms Created project documentation: Operational Guide ENVIRONMENT: Ataccama DQC v.8, Oracle 11g, PLSQL, Bash, Perl
Kinross Gold Corporation, Data Quality Management solution, DQ Lead via Adastra
September 1, 2013 – January 1, 2014
Led a team of developers Created design patterns and development standards Performed Source System Analysis - Data profiling and Assessment Impact of bad data evaluated in collaboration with the Business Provided support in Detail Business Requirements phase Designed and prototyped solution Created Detail Design Specifications Performed development of an Ataccama based ETL and Data Quality Solution: framework to report and correct data quality issues identified from transactional data, Data Quality Measurement system using Data Quality Metrics and custom business rules (Data Quality Dashboards), Issue Resolution system using Data Quality Metrics and custom business rules (Data Stewardship interfaces) etc. Designed and built the orchestration process of the system - PowerShell scripts, workflows Created project documentation: Operational Guide ENVIRONMENT: Ataccama DQC v.8, Ataccama DQD v.8, Ataccama DQIT v.8, MS SQL 2008, Transact-SQL, PowerShell
VivaCom, Data Quality Assessment - DQ Lead via Adastra
May 1, 2013 – June 1, 2013
Led a team of developers Led workshops with the business and IT department Defined data scope gathered and documented data definition (metadata) defined data rules, valid ranges and exceptions Data profiled and analyzed Developed design patterns and standards Implemented Informatica Data Quality mappings to represent and validate the business rules Flagged DQ issues and derived enterprise-wide DQ Indicators and cleansing rules Prepared detail report of findings Created Roadmap, Enterprise Architecture document and estimation (for upcoming project phases) ENVIRONMENT: Informatica Data Quality 9.5, Oracle 10g, PLSQL, PowerShell
VivaCom, Data Quality Pilot Project - DQ Lead via Adastra
November 1, 2012 – December 1, 2012
Gathered and documented requirements Designed and implemented mappings for identifying, validating and deriving contract data Performed unit testing ENVIRONMENT: Informatica Data Quality 9.1 Hotfix 5, Oracle 10g, PowerShell
Empire Life, Single View Of Customer (Enterprise MDM project), ETL/DQ(Data Quality) Lead via Adastra
February 1, 2012 – August 1, 2013
Led a team of developers Created design patterns and development standards Mentored junior developers Source System Analysis - Data profiling and assessment DQ issues confirmed with the Business and documented Impact of bad data evaluated in collaboration with the Business. Provided support in Detail Business Requirements phase - additional analysis, business rules "extraction" Performed ETL Development (Informatica PowerCenter) - source extracts to MDM Hub landing zone data movement and transformations, change capture Informatica Data Quality Development - created data cleansing/parsing/standardization mappings Informatica MDM Hub Development - created Data Model, Stage, Load and Match/Merge processes, Packages, Custom User Exits and scheduling mechanism (Stored procedures) Designed and built the Orchestration process of the system - shell scripts, workflows Created project documentation: Detail Design Specification, Operational Guide ENVIRONMENT: Informatica Master Data Management Hub 9.01, Informatica Data Quality 9.1 , Informatica PowerCenter 9.1, Oracle 11g, IBM DB2, Korn Shell, Perl, PowerShell
CIBC (Canadian Imperial Bank of Commerce) – BI Developer via Adastra
November 1, 2011 – February 1, 2012
Analyzed business requirements and DWH structure Conducted clarification meetings with clients Created new repository subject area for the reporting group – Physical, BMM and Presentation layers (with all relevant elements – aliases, views(select), logical tables, dimensions / hierarchies, measures) Created and embedded analysis in dashboards (with all relevant elements developed – prompts, filters, selection steps, navigations, presentation variables) Created Ibots (delivery) Created SQL statements (expected results), new reports tested and debugged ENVIRONMENT: OBIEE 10g, Windows, Solaris, Oracle 10g DB, SQL Developer
Foresters, DWH Project – ETL Developer via Adastra
August 1, 2011 – November 1, 2011
Analyzed CR requirements Designed solution following best practices Developed ETL code Performed Unit testing and performance optimization Maintained documentation according to developed and tested changes, and optimization ENVIRONMENT: Informatica PowerCenter 9.1, Teradata 13, MS SQL 2005, SQL
Adastra, DWH (Data Warehouse) Project - OBIEE
July 1, 2011 – August 1, 2011
Analyzed business and report requirements Built the Physical, Business Model (and Mapping) and Presentation layers of a repository Created calculation measures (including level–based measures) Created logical dimensions (with level–based hierarchies) Created filters, selection steps Created (and added graphs to) analysis Created dashboards (complete with prompts) Created layouts and reports ENVIRONMENT: OBIEE 11g, Windows, Oracle 11g
CEZ (Leading utility company in Central and South-East Europe) – DQ Specialist via Adastra
June 1, 2011 – July 1, 2011
Analyzed client data Assessed DQ levels Assessed and validated findings and business impacts Prepared DQ assessment report ENVIRONMENT: Ataccama, DB2
Rogers Communications, EDW Release 1.0 – QA Analyst via Adastra
April 1, 2011 – June 1, 2011
Analyzed business requirements Created a complete concept and methodology for the testing process of the Reporting part of EDW project. Standardization of the required documentary forms Ensured the consistency of data flows – tracing of all report elements from BR trough logical and physical data model to source files Created SQL test scripts for all MicroStrategy reports Created ER (Entity–relationship) models for the reports (with data modeling tools) Configured test data generation tools (following the logic of the data) and generation of test data Developed test scripts to ensure uniformity between MicroStrategy results and the expected results (produced by SQL) Generated test cases and test scripts (both SQL and Korn Shell) for each of the reports Developed custom tools (expert shell and Visual Basic programming) for optimization of time–consuming manual activities, i.e.: comparison between documents, searching and tracing data (in mapping documents for example), generation of test scripts and cases etc Prepared and delivered trainings on specific principles and technologies of Report testing – good practices, ways of optimizing the process, expert SQL and shell programming techniques ENVIRONMENT: IBM AIX, Teradata 12, Informatica PowerCenter 8.6, MicroStrategy 9, SQL, Korn Shell, PowerShell, Visual Basic for Applications
Adastra, BI Project – Microstrategy
February 1, 2011 – March 1, 2011
Analyzed business and reports requirements Analyzed database analytical layer Created Metadata database Created logical data model: facts, attributes, hierarchies, metrics Designed reports: created drill down and standard reports, dashboards, scorecards Performed unit testing and supported client testing ENVIRONMENT: MicroStrategy 9, Windows, Oracle 11g
Data Science Specialization by Johns Hopkins University
Coursera
June 24, 2026 – Present
Data Science Capstone by Johns Hopkins University
Coursera
June 24, 2026 – Present
Developing Data Products
Johns Hopkins University
June 24, 2026 – Present
Practical Machine Learning
Johns Hopkins Bloomberg School of Public Health
June 24, 2026 – Present
Regression Models
Johns Hopkins Bloomberg School of Public Health
June 24, 2026 – Present
Statistical Inference
The Johns Hopkins University
June 24, 2026 – Present
Talend Data Integration Advanced (DI-102-v62)
Talend
June 24, 2026 – Present
Talend Data Integration Basics (DI-101-v62)
Talend
June 24, 2026 – Present
Reproducible Research
The Johns Hopkins University
June 24, 2026 – Present
Exploratory Data Analysis
The Johns Hopkins University
June 24, 2026 – Present
Getting and Cleaning Data
The Johns Hopkins University
June 24, 2026 – Present
R Programming
The Johns Hopkins University
June 24, 2026 – Present
The Data Scientist’s Toolbox
The Johns Hopkins University
June 24, 2026 – Present
Velocity Best Practices and Implementation Methodology for Data Integration 9.X
Informatica University
June 24, 2026 – Present
Informatica Data Quality Developer v9.x (Associate)
Informatica University
June 24, 2026 – Present
Informatica Master Data Management (MDM) Hub Developer v9.x (Associate)
Informatica University
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project experience across various industries (finance, telecommunications, gaming, retail) and consulting roles at Adastra suggests adaptability and a broad understanding of different business contexts. Their progression into leadership and practice lead roles indicates ambition and a commitment to growth. The involvement in a Kaggle competition and continuous learning through certifications demonstrate a proactive and innovative mindset, which aligns well with a dynamic, growth-oriented culture. The target role of 'AI Engineer' aligns with their recent focus on Machine Learning and Data Science, indicating a clear career trajectory.
Soft Skills & Operational Fit
The candidate's resume highlights strong leadership, mentoring, and client engagement skills, indicating a good operational fit for roles requiring team management and stakeholder interaction. Their experience in defining design patterns and development standards suggests a focus on best practices and process improvement. The ability to translate business requirements into technical solutions and present findings indicates strong communication and problem-solving skills.