DataOps
01Practices
DataOps, MLOps and AIOps
Operating models, observability, automation and release discipline that help enterprise data and AI teams deliver reliably.
Delivery systemsObservabilityGovernance
Team Lead, Data & AIE.ON Software DevelopmentEurope
Profile / Vlad Masek
Enterprise data practices, platforms and applications.
I help organizations turn ambitious data and AI programs into engineered, operable systems. My work combines technical leadership, architecture, consulting, teaching and public speaking.
- Current role
- Team Lead Data & AI Chapter at E.ON Software Development
- Public direction
- Speaker CodeCamp Iasi 2025
- Education
- Workshops NGO and professional learning
Value layers
What the DevBurger practice delivers.
Helping organizations build reliable data and AI platforms, strengthen engineering practices and grow the teams that operate them.
02Platforms
Cloud platforms, data fabric and mesh
Pragmatic architectures for governed data products, domain ownership and interoperable analytics and machine learning workloads.
AWSData FabricData MeshData products
03Applications
From data to useful systems
Engineering leadership that connects architecture to the applications, decisions and experiences people actually use.
ArchitectureAI systemsTechnical leadership
Capability profile
Deep engineering capability across the modern data stack.
A self-assessed view of professional depth based on hands-on delivery, architecture and engineering leadership. Scores describe working capability rather than certification count.
01
Operate what you build. Delivery quality, observability and ownership are architecture concerns.
02
Teach the system. A platform succeeds when teams can understand, adopt and extend it.
03
Connect the layers. Data engineering, ML and operations should reinforce one another.
Evidence-led capability profile
0110/10
Data Engineering
Production-grade platforms, pipelines and data quality systems.
PlatformsPipelinesQuality
0210/10
Backend Engineering
APIs, services and distributed systems built for real operations.
ServicesAPIsDistributed systems
039/10
Cloud Architecture
Cloud foundations that connect delivery speed with governance.
AWSArchitectureGovernance
049/10
Database Engineering
Data models and stores designed for performance and reliability.
ModelingPerformanceReliability
059/10
Data Platforms / DataOps
Operating models that make data products observable and adoptable.
Data productsObservabilityOperations
068/10
Applied Data Science
Analytical and machine learning practice grounded in delivery.
ModelingAnalyticsML delivery
Technology signals
Hands-on experience across cloud, data and software engineering.
As of July 2026
Affinity reflects depth of practical use across architecture, delivery and operations.
Technology indexExplore stack affinity
Technology12345678910Affinity
01 / CloudAWS10/10
02 / LanguagePython10/10
03 / DeliveryCI/CD & automation9/10
04 / DataSQL & relational databases10/10
05 / PlatformKubernetes & OpenShift8/10
06 / CloudGoogle Cloud8/10
07 / Search & opsElastic Stack8/10
08 / BackendFastAPI & Flask9/10
09 / Applied AIML frameworks8/10
10 / DataSpark & PySpark9/10
11 / Big dataHadoop & Hive8/10
12 / LanguageGo8/10
13 / PlatformDocker9/10
14 / OrchestrationAirflow & MageAI9/10
Working depth Lead stack
Speaking
Practical ideas for engineering audiences.
Conference talks and technical sessions on enterprise data architecture, DataOps, MLOps and the realities of operating modern data platforms.
available
AIOps as an engineering practice, not a dashboard category
Available for events and summits
Europe / remote
AIOpsObservabilityOperational intelligence
delivered
From pipelines to platforms: making data engineering operational
CodeCamp Iasi 2025
Iasi, Romania
DataOpsData platformsEngineering leadership
Workshops
Practical workshops for data and engineering teams.
Instructor-led sessions on data platforms, DataOps, MLOps and engineering practices, supported by durable HTML and PDF materials.
WorkshopFull-day
Building governed data platforms on AWS
Hands-on architecture patterns for S3 data lakes, Glue, Lambda, Step Functions, Athena, Lake Formation and federated access.
WorkshopHalf-day or full-day
DataOps foundations for enterprise data teams
A practical workshop on delivery patterns, orchestration, testing, observability and release discipline for data products.
WorkshopFull-day
MLOps for data engineers
A bridge between production data engineering and model operations, focused on feature pipelines, lineage, quality and deployment boundaries.
Writing
Field notes on building and operating data platforms.
Articles on platform architecture, DataOps, engineering leadership, workshops and lessons carried from delivery into practice.
Writing index →Data platformsDataOps
Platform thinking for data engineering teams
A placeholder for future writing on the shift from pipeline delivery to product-oriented data platforms.
Speaking notesComing soon
From conference stage to practical playbook
A repeatable format for turning technical talks into useful engineering references.
Education
Technical education with social reach.
The education work gives DevBurger a purpose beyond commercial delivery: helping people build confidence through practical engineering knowledge.
CurrentLuxembourg
WeStem
Educational contributorNGO-based educational work that helps emerging technical talent build confidence with data, engineering and AI-adjacent concepts.
PastRomania / online
SkillLab
Online instructorData engineering instruction through digital learning platforms, with an emphasis on practical concepts and applied technical growth.
Open workshop library
A future edu.devburger.nl surface for Revel-generated workshop material, labs and presentation-ready PDFs.
View education direction →DevBurger / Vlad Masek
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