Open to work
Remote / hybrid in Europe
Real-time data systems
Junior Data Engineer
Junior data engineer focused on real-time data systems, telemetry, and monitoring.
Hands-on experience building an MQTT-based live monitoring system at Sonaca, backed by 9 years in critical infrastructure where reliability, failure handling, and operational response mattered every day.
Python
SQL
MQTT
Kafka learning path
Live operational data
Operational reliability
Explore
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Use these buttons to jump directly to proof, experience, skills, focus, or contact details.
Case Study
Live data case study
Sonaca is the strongest proof point: a final-year academic project developed in collaboration with Sonaca and IETC, built around MQTT telemetry received twice per second, real-time dashboards, and real operational stakeholders.
The problem
Operational stakeholders had to physically access machines to check live metrics. Critical parameters were invisible until someone walked the floor, and anomalies were discovered too late.
What I built
A proof-of-concept real-time monitoring application that brought machine telemetry to dashboards, with threshold alerts and historical SQL validation for operational decision-making.
The result
Operational stakeholders could see system status at a glance. Anomalies triggered instant visual alerts instead of delayed manual checks.
Before
Operational stakeholders walked machines to check live metrics.
After
Real-time dashboard with automatic alerts and validation.
Featured project
Real-time telemetry and monitoring at Sonaca
Designed and built the application layer for a real-time data ingestion and monitoring proof of concept, connecting to the existing Siemens BFC Gateway via MQTT to process live telemetry from connected machines in an aerospace manufacturing environment.
The system processed machine data received twice per second via MQTT, using a 500ms telemetry update interval to transform JSON payloads into structured application entities and deliver real-time visibility through threshold-based alerts and SQL-backed historical validation.
The OT infrastructure, including the BFC Gateway, AVEVA Historian, network, and machines, already existed. My work focused on the application layer (built on the company's Mendix platform), MQTT ingestion, JSON processing, dashboards, alerts, and SQL validation; the proof of concept was functionally validated and delivered internally to the IT team.
Transferable patterns
Live ingestion, reconnection handling, alerting, state persistence, historical validation, and dashboards for fast operational decisions.
Where this fits
Monitoring platforms, telemetry products, event-driven backend systems, infrastructure data flows, and operations-heavy analytics.
Why it travels well
The value is not limited to industrial settings. The same design patterns apply anywhere live data needs to stay reliable, visible, and actionable.
Open technical details and GitHub activity
What I built
- MQTT subscription flow for continuous telemetry ingestion
- Telemetry processing for data received twice per second
- Asynchronous in-memory model for latest machine values
- Fallback logic to preserve last-known values during connection loss
- Threshold-based alerting using configurable machine parameters
- SQL validation against historian data for troubleshooting and comparison
- Role-based access patterns for operator and supervisory views
- Dashboard navigation by production area, machine, and sensor
Technical environment
MQTT
JSON
SQL
AVEVA Historian
2Hz telemetry stream
Alert logic
Agile/Scrum
IEC-62443 context
Active on GitHub
Building in public, one proof point at a time.
GitHub is where architecture notes, portfolio projects, and public work are gradually turning into stronger case studies.
- Sonaca monitoring architecture and documentation
- Zoomcamp projects as they become portfolio-ready
- Consistent public progress instead of one-off demos
Portfolio direction
More deployable data projects are coming next.
This portfolio will keep expanding with public projects around orchestration, warehouse modeling, and streaming ingestion patterns as they become portfolio-ready.
Same patterns, other domains
Reliability patterns travel beyond one environment.
Safe ingestion, reconnection handling, last-known-value persistence, and threshold alerting are domain-independent. The same real-time patterns can apply to patient monitoring, fintech fraud detection, logistics tracking, and any system where live data must remain accurate, visible, and trusted.
In healthcare-adjacent contexts, this means transferability to healthcare operations and connected health scenarios such as device uptime monitoring, operational dashboards, alerting, and non-clinical telemetry workflows.
Experience
Relevant experience
Final academic project
Sonaca
Built the application layer of a real-time monitoring proof of concept for a high-reliability environment, with live telemetry ingestion, historian validation, and dashboards designed for operational review.
- Telemetry ingestion through MQTT
- Telemetry data received twice per second
- SQL-based historian validation
- Dashboard design for operational stakeholders
Previous career
Water infrastructure field operations
Worked in environments where reliability, maintenance discipline, traceability, and practical incident response were central to daily operations.
- Critical infrastructure operations
- Maintenance discipline and troubleshooting
- Process awareness and accountability
Education
Bachelor's in Applied Computer Science
Transitioned into software and data systems with a clear interest in streaming, data pipelines, and operational digital systems.
- Applied Computer Science degree completed in 2025
- Data-oriented systems and software foundations
- Bridge from operations into engineering
Skills
Tech stack & tools
Core competencies in Python, SQL, and real-time messaging, with active expansion into distributed streaming systems.
Programming & data
Python, SQL, PostgreSQL, Git, Linux, data modeling basics
Messaging & ingestion
MQTT, JSON payload processing, REST APIs, real-time telemetry flows
Platforms & workflow
Docker, Azure exposure, Agile/Scrum, operations-heavy collaboration contexts
Currently learning
Currently completing the DataTalksClub Data Engineering Zoomcamp with focus on Kafka, Spark Streaming, and distributed systems.
Where This Fits
Relevant across more than one domain.
The current profile fits teams working with live data, operational visibility, and event-driven systems, not only industrial use cases.
Monitoring & observability
Live dashboards, alerting flows, anomaly visibility, uptime monitoring, infrastructure observability, product monitoring, and support operations.
Telemetry & connected systems
MQTT ingestion, device and event telemetry, connected systems, connected health devices, IoT platforms, state handling, and message-driven flows.
Event-driven backends
Streaming pipelines, asynchronous processing, real-time validation, durable state, fintech event flows, healthcare data integration, and API-backed data products.
Operational data systems
Systems where data supports fast decisions for operational teams, support teams, hospital operations, logistics tracking, utilities, and service delivery.
Background
From field operations to data engineering.
Nearly a decade in water infrastructure came before the move into software and data systems. That background shaped a practical way of thinking about uptime, failure modes, and reliable monitoring.
What shapes my approach
Systems should stay reliable under real-world pressure.
An operational background shapes the approach to data engineering: ingestion should be dependable, monitoring should be actionable, and pipelines should support real decisions.
Why This Profile Stands Out
Proof points that come from real systems, not only coursework
Experience-led proof points focused on uptime, graceful degradation, operational constraints, and real streaming systems.
01
Operational intuition from 9 years in the field
Years in critical infrastructure built strong instincts around uptime, failure modes, and what reliability actually means when response time matters.
At Sonaca: designed MQTT reconnection logic and last-known-value persistence because connections fail and systems need graceful degradation.
02
Real hands-on experience with streaming-style data
Project work included a system processing live MQTT telemetry received twice per second in a high-reliability environment with IEC-62443 security considerations and real operational stakeholders.
Final-year academic project built for a real high-reliability environment and validated with operational stakeholders.
03
Experience with live operational data systems that is rare in juniors
Comfortable at the boundary between operational systems and data pipelines, where live data, dashboards, reliability requirements, and technical constraints meet.
Able to translate between technical teams, operators, and stakeholders. That boundary exists in industry, but also in health-tech, fintech, logistics, and monitoring products.
What this means for you
You get a junior who already understands live operational contexts, streaming constraints, and why resilience and monitoring matter.
Direction
Current focus
Practical growth toward real-time data engineering through public projects, streaming systems, and reliable data pipelines.
What I'm working on
Building toward real-time data engineering
Current work is focused on real-time data engineering through public projects: streaming ingestion, orchestration, warehouse modeling, and reliable data workflows.
The DataTalksClub Data Engineering Zoomcamp supports that direction, with focus on Kafka, Spark Streaming, and distributed systems. New projects are added to GitHub as they become portfolio-ready.
Long-term direction: grow into real-time and streaming data engineering roles where live data, reliability, and operational visibility matter.
Languages
Romanian, English, French
Romanian native speaker, fluent English, and French at C1 level.
Contact
Contact
Open to junior data engineering roles in streaming, telemetry, and operational data systems.
Email
georgescumvlad@gmail.com
LinkedIn
linkedin.com/in/vlad-georgescu-dev
GitHub
github.com/vladgme
Location
Belgium · Remote or hybrid within Europe
Open to
Junior Data Engineer · Streaming · Telemetry · Operational Data