Data Engineering
I design pipelines that move, validate, transform, and serve data reliably for analytics and operations.
ETL pipelinesData validationAWS GlueS3 + AthenaStep FunctionsTerraform
Data Engineer | Data Scientist | Technical Writer
Building data systems people can trust, use, and understand.
I build scalable data pipelines, extract actionable insights with statistics and machine learning, and document complex systems so technical and business teams can make better decisions.
4+
years in data roles
18+
technical tutorials
40+
students mentored
95%+
accuracy focus in client insight delivery
Current focus
Python, SQL, AWS ETL, Power BI, ML modeling, and data education.
Based in
Vilnius, Lithuania. Working across analytics, data platforms, and technical writing.
What I do
Three disciplines, one workflow.
My best work happens where data engineering, data science, and communication overlap: build the system, analyze the signal, explain the result.
Data Science
I use statistical modeling and machine learning to answer business questions and make trade-offs visible.
Machine learningPricing analysisExperimentationForecastingModel evaluationResponsible AI
Technical Writing
I turn technical systems into tutorials, documentation, and explanations people can actually use.
DataCamp tutorialsAPI-style docsNewsletter writingModel cardsGuidesDeveloper education
Featured projects
Case studies, not just repository links.
Pipeline pattern
How I architect data products: reliable flow, visible decisions, useful outputs.
Data Engineering
AWS Survey & Ad-Awareness ETL Pipeline
Problem
Survey and ad-awareness data needed repeatable ingestion, transformation, validation, and query-ready outputs.
Solution
Built a Terraform-managed AWS workflow with Glue, S3, Athena, IAM, EventBridge Scheduler, and Step Functions.
Impact
Created an automated, reviewable pipeline across bronze and silver layers with documented resource flow and data checks.
PythonAWS GlueS3AthenaStep FunctionsTerraform
Python Engineering
Legacy Integration Pipeline Modernization
Problem
A large legacy integration workflow created operational friction and required too much manual handling.
Solution
Modernized the Python codebase, added multi-format ingestion, SFTP/FTPS handling, S3 delivery, logging, and monitoring.
Impact
Reduced manual operations workload by about 40% and improved consistency for downstream reporting datasets.
PythonSQLpandasSFTPAWS S3pytest
Problem
A recommender-style model needed transparency around bias, fairness trade-offs, and threshold decisions.
Solution
Built a reproducible scikit-learn pipeline with MLflow tracking, fairness metrics, reweighing, threshold sweeps, and a Streamlit app.
Impact
Produced governance-ready artifacts including a model card, data sheet, risk assessment, and trade-off summary.
PythonScikit-learnMLflowStreamlitFairness metrics
Data Science
Brand Tracking & Pricing Analytics
Problem
Global brand teams needed clearer pricing, perception, and campaign-performance insights across multiple markets.
Solution
Delivered Power BI dashboards, SQL models, CVI/CBI computations, MaxDiff, Van Westendorp, and key driver analysis.
Impact
Supported client-facing decision-making with 95%+ data accuracy targets and 15-20% pricing strategy precision improvements.
Power BISQLPythonDAXMaxDiffVan Westendorp
Writing & publications
Technical writing is part of the work.
I write tutorials, explainers, and newsletters that make data engineering, analytics, machine learning, and AI ethics easier to understand and apply.
PythonDataCampPractical read
Python Circular Import: Causes, Fixes, and Best Practices
A practical breakdown of circular imports, why they happen, and how to restructure Python code cleanly.
Read articleMachine LearningDataCampPractical read
Linear Regression in Python
A hands-on guide to the core ideas behind linear regression and how to implement them in Python.
Read articleSQLDataCampPractical read
Normalization in SQL
Explains database normalization from 1NF to 5NF with examples for cleaner and more reliable schemas.
Read articleNewsletterSubstackPractical read
All About Data & More
A newsletter for aspiring data professionals, covering data analytics, machine learning, SQL, and job-ready workflows.
Read articleExcelDataCampPractical read
How to Make a Bar Graph in Excel
A beginner-friendly guide to building clear Excel bar charts for reporting and analysis.
Read articlePythonDataCampPractical read
Python Inheritance: Best Practices for Reusable Code
Covers inheritance in Python with examples that make object-oriented programming easier to apply.
Read articleTech stack
Grouped by how the work gets done.
No percentage bars. The stack is organized by the job it performs: pipelines, modeling, dashboards, applications, and writing.
Data Engineering
PythonSQLpandasAWS GlueS3AthenaStep FunctionsEventBridgeTerraformSSIS
Data Science
Scikit-learnStatisticsModel evaluationFeature importanceExperimentationPricing modelsResponsible AI
Analytics & BI
Power BIDAXKPI designData modelingCVI/CBIMaxDiffVan WestendorpDashboard design
Apps & Writing
StreamlitLangChainOpenAI APITechnical tutorialsDocumentationModel cardsData sheetsCurriculum design
Experience
A career built around data work that ships.
2025 - Present
Data Scientist
Syno International
Building ETL workflows, AI-powered internal tools, Power BI outputs, and statistical models for survey, brand, and pricing analytics.
2024 - 2025
Data Analyst
Syno International
Delivered dashboards, SQL models, pricing studies, brand equity analysis, and client-ready insight workflows across multiple markets.
2024 - 2025
Technical Writer
DataCamp
Published peer-reviewed tutorials on Python, SQL, Excel, statistics, machine learning, and practical data concepts.
2023 - 2024
Data Science Instructor
GOMYCODE
Taught and mentored 40+ students through Python, SQL, machine learning, visualization, and end-to-end data projects.
2020 - 2024
BI Specialist / Data Scientist
Freelance
Built dashboards, ETL processes, documentation, and analytical solutions for clients across energy, finance, and edtech.