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(Uppdaterat 2020-04-30)Data Engineer, Full-stack developer
Stockholm, Sweden
Modersmål English
- Python, Go, Node, TypeScript, React, Bash, Linux
- Strong full-stack developer
- Data Engineering in AWS
Kompetenser (52)
Backend Developer
DynamoDB
Scientist
AWS
Molnarkitektur
AWS stack
REST
NoSQL
ENGINEER
data
Node.js
AMAZON DYNAMODB
AI/ML
DATASETS
AWS Lambda
ARCHITECTURE
Skriptning
React
DATA SCIENCE
Infrastuktur som kod
HTML/CSS/JavaScript
JavaScript
Python
LOGGING
AWS API Gateway
Machine Learning
DATA INTEGRATION
NEURAL NETWORKS
PostgresSQL
Data Analysis
DevOps
Data Engineer
PIPELINE
COLLECTION
GCP
ETL
Java/Kotlin
Data Scientist
SQS and S3
Clojure
frameworks
Elasticsearch
CloudFront
Experience
Kafka
REAL-TIME
golang
SQL
DATA COLLECTION
SNS
REDIS
NETWORK DESIGN
Sammanfattning
Victor is a diverse engineer with experience from both the quick-paced startup world, as well as from large
corporations. Starting his career from a high-performance computing education, Victor worked with complex
machine learning tasks and understood quickly the importance of mapping the customer need to the technical
delivery. On a daily basis he works as a Fullstack engineer and a Data engineer, focusing on data-driven
applications where both frontend and a well-architected backend is of the greatest importance. He speaks
cloud natively and always has an end-to-end mindset when designing data pipelines or event-driven
architectures.
Roles Selected assignments
Data engineer
Data scientist Lead Fullstack Engineer -- AgoyIt
Fullstack Engineer AgoyIt is a fintech startup in the accounting sector
Frontend developer challenging the large enterprise software
App developer corporations in the nordic. Victor leads a team of
Backend developer three developer building a complete event-driven
Lambda architecture in AWS, to serve thousands of
Professionell bakgrund
2019-10 - Pågående
company offers smarter workflows and a cloud-based solution that simplifies the work for thousands of accounting consultants across the nordics.
Victor entered AgoyIt as the first developer, establishing the technical architecture, mapping product and user
requirements to the overall solution. He created an MVP of the software that rose a funding round of 2 MSEK.
He then recruited a larger team which he led to build and deploy the first version of the product to the nordic
market. The application is built in React and Typescript with a backend in AWS, using GraphQL, Lambdas and DynamoDB as storage solution.
Victor also took the initiative of setting up the ETL pipelines for the raw data using AWS Glue (Spark) with the purpose of being able to serve aggregated data from GraphQL to the end users, giving organizational
oversight as well as datasets for upcoming machine learning projects for automation purposes.
Overall, the deployed product offers a diversity of features, including payments, advanced content caching
due to large amounts of images, real-time collaboration with GraphQL subscriptions and role-based sharing and reporting opportunities.
Keywords: React, Typescript, GraphQL, Apollo, DynamoDB, Spark, Glue, S3, Python, Golang, Jenkins,
Terraform, CI/CD, Product development, Scrum, Systems architecture
2019-04 - 2019-10
stations as well as radio and auxiliary services.
Victor joined Ericsson in a full-stack development team, focusing on internal interfaces that supports in-house
capabilities among different teams in the data analysis sector. Victor worked heavily with React development
using Cypress, Jest and a TDD mindset in an agile team. The team utilizes Ericssons internal cloud solutions as well as more common open-source software like Jenkins, Docker and Kubernetes clusters for CI/CD, which
Victor was part of developing as well with the backend team.
Keywords: React, Redux, Javascript, Jenkins, Jest, Cypress, Docker, Kubernetes
2019-02 - 2019-05
Victor architected an event-driven GCP architecture that could act as the central decision hub for a fleet of IoT
devices. The devices collected data continuously from water tanks on PH-levels, temperature etc. and was
then controlled by the central hub to adjust parameters in the water.
The backend was designed in Lambda fashion, to allow for a fast response track, utilizing Redis and SQL to update the React dashboard, also built by Victor. The other track fed data through Kafka into buckets, where
future data science teams could use the data to create smarter control systems for the farms.
Keywords: GCP, IoT, Python, Spark, PostgreSQL, Serverless, Redis, Kafka, Product development, System
design, React, Jest, NodeJS, Express, Netlify, REST
2018-10 - 2019-02
10000 members where companies can connect with talents that have desired knowledge and experience.
Victor came in as a backend developer, working mainly in Elastic Beanstalk applications using Clojure. His
focus was on improving the data integration, data cleaning and the presentation between customer service and end users, using Intercom. He also initiated a project for using a central logging system in the company's
cloud environment using the ELK stack, templating it with Terraform and Ansible, which is now used company
wide.
Keywords: AWS, Clojure, JavaScript, MySQL, MySQL Workbench, Integration, Functional Programming,
Docker, Docker Compose, Ansible, Terraform, Elasticsearch, Kibana, Logstash
2018-08 - 2018-10
scooter at any time and go ride around the city, completely free from emissions.
Victor's role was to help the hardware team develop an interface and software in order to make the initialization of the scooters faster but also reduce the risk of damaging the scooter during that process. The
software was developed in Python containers running in Kubernetes on Google Cloud. The project resulted in a an interface that significantly reduced the fault tolerance of the communication between backend services and the scooters and is now used during the production of Voi Scooters.
Keywords: Python, PyQt, PostgreSQL, GCP, Kubernetes, Docker, Micro-services
2018-03 - 2018-08
friend with the help of machine learning. The idea is for the unit to learn the dogs behaviour and to give the dog owner better insights into the dogs well-being.
The company wanted a basis for a suitable machine learning model to be able to determine a dog's activity.
Among the challenges was to make a model with good generalisability for dogs of different sizes and also make the collar independent of position.
Victor had a key role in the implementation and evaluation of different machine learning models in order to develop a model that could distinguish different patterns in a dogs behaviour using sensor data. The project
involved Spark ETL on the raw data and feature selection from the time and frequency domain. The evaluated
models consisted of Feed Forward and Convolutional Neural Networks, implemented in TensorFlow in Python, as well as other machine learning methods, such as, Random Decision Forests, k-NN and SVM by using
Scikit-learn. The project resulted in a model which could determine whether the dog is resting, walking,
playing, eating or peeing.
Keywords: IoT, Spark, ETL, Python, Machine Learning, Neural Networks, Deep learning, Time-series
modelling, TensorFlow, Scikit-learn, Azure, Linux, Docker
2017-01 - 2018-03
friend with the help of machine learning. The idea is for the unit to learn the dogs behaviour and to give the dog owner better insights into the dogs well-being.
Tracy Trackers has developed a real-time application which utilizes machine learning. A fast inference speed
is crucial for a model which is used for a real-time application because it has a big impact on the user
experience. This demands a lot of optimisation of the whole data flow in the product.
Victor was part of developing and evaluating different frameworks and techniques to optimize data storage and transfer on embedded devices, machine learning inference as well as cloud architecture. He worked
close together with the firmware team and the CTO to develop a data collection iOS app in order to create a
complete data pipeline from embedded device up to the cloud and back to the app.
Keywords: Python, Azure, Docker, Machine Learning, iOS development, Data engineering, Systems
architecting, Network design, Bluetooth LE, Edge computing
Educations, courses and certificates
MSc. High-performance computing, Major in Machine Learning
BSc. Media Technology, Minor in Machine Learning