Mycodata — Data Systems Engineering

Our Capabilities

Engineering systems across the data lifecycle.

We design, build, and maintain production-grade data and software systems.

Data Infrastructure & Engineering

ETL / ELT pipeline design
Data modeling and schema design
API and system integrations
Batch and event-driven processing

Automation & Custom Systems

Workflow and process automation
Custom internal tools and Power Apps
Scheduled and event-based jobs
Microsoft 365 & platform integrations

Business Intelligence & Reporting

Power BI dashboards and data models
Automated report generation at scale
KPI definition and metric tracking
Data validation and quality checks

Data Science & Machine Learning

Predictive and classification models
Forecasting and optimization
Feature engineering pipelines
Model deployment and monitoring

Case Example

Automated mass reporting at production scale.

Context

A research firm needed to deliver individualised PDF reports to 2,000 survey participants, with tailored results for each participant. Producing them by hand was infeasible — the volume alone ruled out any manual process, and the turnaround window was tight.

Solution

We built a fully automated pipeline: survey data ingestion and validation, per-participant report templating, and batch-rendered PDF generation at scale — producing a personalised, branded report for every respondent without a single manual step.

Outcome

2,000+

reports generated

0

manual touches / run

↺

repeat client

The client returned for follow-up work — the system delivered exactly what was promised, on schedule.

Who We Are

Engineers behind the systems.

Dániel Raksányi

Co-Founder // Data Systems

I started Mycodata to build the kind of data systems most businesses are told are out of reach — fraud detection, credit scoring, forecasting, and the pipelines that hold it all together. With a background in Physics and years spent leading a data team and shipping machine learning and cloud infrastructure into production, I care about one thing: systems that actually run, without you having to babysit them. When you work with us, you work directly with the people building it.

Python SQL AWS ML dbt MLflow

Márton Király

Co-Founder // BI & Finance Systems

I spent over a decade in audit, controllership, and financial consulting — including years at EY — before turning that experience toward data. As a Certified Public Accountant and Certified Fraud Examiner, I bring audit-grade rigour to everything we build: BI dashboards that reconcile, controlling systems that hold up, and reporting people can actually trust. I've led BI teams and designed reporting frameworks from the KPI up. My job is making sure what we build answers the real business question — not just the technical one.

Power BI DAX SQL Python Power Automate CPA · CFE

Dániel Erős

Data Engineer // Performance & Architecture

With a Master’s in Applied Mathematics and a track record across finance and manufacturing, I build high-performance data architectures that directly improve the bottom line. In my most recent role, I re-engineered on-premise SQL Server environments to cut daily load times from 10 hours to 5 minutes and p95 query times from 15 minutes to 10 seconds. Earlier, consulting for BMW via Palantir Foundry, my pipeline optimizations delivered $4,000 in monthly savings. As Mycodata’s founding Data Engineer, I turn that focus on performance and cost into scalable systems that drive real profitability — for us and our clients.

SQL Server Palantir Foundry ETL / Pipelines Performance Tuning Data Modeling

Valter Hunyadi

Data Engineer // Cloud & Pipelines

For the last few years I've built and run the data infrastructure behind a Hungarian payment institution — the ingestion pipelines and cloud warehouse everything downstream depends on. There I implemented core layers of the migration to a modern AWS stack, owning the Airbyte ingestion, Dagster orchestration, and dbt modeling. Earlier I tuned high-volume analytics platforms that handled billions of rows and daily loads in the tens of millions. I also built internal AI tooling on top of Claude — automated code review and test generation — that kept our own delivery fast. My focus is simple: data that arrives on time, every time, without surprises.

Python SQL AWS dbt Dagster Airbyte

When projects demand it, we bring in trusted specialists from our network — there is very little we cannot take on.

// System_Sequence

A modular engineering flow.

01_ANALYSIS

Requirement Mapping

Understanding your data landscape and defining what success looks like.

02_ARCHITECT

Flow Design

Mapping the right architecture before writing a single line of code.

03_ENGINEER

Production Build

Building systems that handle real data, edge cases, and load from day one.

04_DEPLOY

Final Integration

Delivery, handover, and ongoing support — you own what we build.

Contact Us

Let’s secure your data infrastructure.

Ready to automate your workflows or scale your data engineering? Send us a brief overview of your challenge.

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Now taking on new projects — available Q2–Q4 2026

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Response within 24 hours

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Free scoping call — no commitment

info@mycodata.hu

We turn your data problems into automated, reliable systems.