About Radoslav
Data Engineer & Analytics Consultant | Databricks, AWS, Iceberg, Python, SQL, Power BI
I help companies design, build, and improve modern data platforms, analytics pipelines, and reporting solutions. My work focuses on turning raw, fragmented, or manual data processes into reliable, scalable, and business-ready data products.
I specialize in data engineering, cloud data architecture, and analytics delivery, with hands-on experience across Databricks, AWS, Apache Iceberg, Python, SQL, Power BI, and modern data lakehouse patterns. I can support projects ranging from ETL/ELT pipeline development and data modelling to dashboard delivery, automation, and performance optimization.
I work best with companies that need practical, end-to-end data solutions: ingesting data from APIs or files, transforming and modelling it, organizing it in cloud storage or lakehouse tables, and making it available for reporting, analytics, or downstream systems.
Areas I can help with:
Data engineering and ETL/ELT pipelines
Databricks notebooks, workflows, and lakehouse development
AWS-based data solutions
Apache Iceberg table design and optimization
Python automation and data processing
SQL development and performance tuning
Power BI dashboards and semantic models
Data modelling for analytics and reporting
API data extraction and integration
Data quality checks and pipeline monitoring
Migration from manual Excel-based workflows to automated data processes
My approach is pragmatic and business-focused: I aim to deliver solutions that are clean, maintainable, scalable, and easy for teams to understand and operate.
Slovak
Native or bilingual
English
Fluent
Remote only
Primarily works remotely
Experience
- GoodData —Business Intelligence ConsultantMarch 2025 - Today (1 year and 5 months)Designing and building a data platform on open table formats (Apache Iceberg) within the AWS ecosystem —from ingestion layer through transformation to curated output Implementing ingestion patterns including batch processing, metadata-only ingestion, and configuration-driven load types using Spark SQL and PyIceberg Working with multiple Iceberg catalog implementations, evaluating tradeoffs between flexibility and standardization in production Contributing to data architecture decisions, data modeling, and pipeline reliability across the platform
- Resulmatic (formerly Aures Apps)Data Warehouse and Quality Team LeaderJanuary 2023 - February 2025 (2 years and 1 month)Prague, CzechiaLed a team responsible for data warehouse development, data quality, and reporting delivery across multiple client environments Managed design and development of SQL-based ELT pipelines for Azure Synapse and Databricks Oversaw implementation of dbt transformation layers and Power BI reporting datasets Established data quality monitoring, governance processes, and operational standards Coordinated cross-team project delivery and client communication
- Resulmatic (formerly Aures Apps)Data Operations Team LeaderJune 2021 - December 2022 (1 year and 6 months)Prague, CzechiaTransitioned from individual contributor to team lead, managing data operations across multiple client projects Defined operational processes for data delivery, monitoring, and incident response Supported the team's development from ad-hoc reporting to structured data operations
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Education
- Master's degree in Economics and FinanceCharles University, Institute of Economic Studies2019Master's degree in Economics and Finance
- Bachelor's degree in Business ManagementMendel University2016Bachelor's degree in Business Management