As a seasoned software and data engineer, I bridge the gap between technical innovation and business value across some industries. From automotive to e-commerce, I've navigated the wide spectrum of technological environments—from legacy systems to cutting-edge cloud architectures. My engineering philosophy centers on creating maintainable, thoughtfully designed solutions that deliver lasting impact.
My expertise spans the entire data lifecycle, transforming raw information into actionable business intelligence through well-architected pipelines and even intuitive dashboards. Beyond technical implementation, I've cultivated leadership skills through building and guiding cross-functional teams toward shared objectives.
With a passion for natural language processing (NLP) that extends into my personal projects, I'm currently immersed in the rapidly evolving AI landscape, tracking emerging trends and exploring innovative architectural and technical approaches. In 2024, my focus has expanded to include generative AI technologies and their practical applications within enterprise environments.
Core technical expertise:
Working for VFC as a contractor on VF Analytics Platform
Delivering AWS solutions for data pipelines. Building out a data lake in Redshift for brands like The North Face, Vans, Timberland, Dickies, Smartwool, icebreaker. Transforming data into value through dashboards, which can provide as a compass for business decisions.
In 2025 work is happening in both Azure Databricks and on the AWS front. I am focused on data engineering and generative AI.
Working for BMW as a contractor on Cloud Data Hub - Applied Connected Vehicle
BMW Group decided to re-architect and migrate its on-premises data lake to the cloud using Amazon Web Services (AWS) in order to innovate and scale for its global stakeholder demand. The company's Cloud Data Hub (CDH) processes and combines anonymized data from vehicle sensors and other sources across the enterprise to make it simple for internal teams to create customer-facing and internal applications.
AWS Case Study: https://aws.amazon.com/solutions/case-studies/innovators/bmw/
Delivering AWS solutions for data pipelines and exposing data over API-s. Writing Infrastructure as Code with Terraform, building API-s & ETL-s with Python, Scala & Apache Spark. Heavily using a set of the AWS resources: Lambda, Gateway, Athena, Glue, Step Functions / State Machines, DynamoDB, S3, CodePipeline, CodeBuild and more.
Worked for the biggest online food ordering company from the US as team augmentation and using microservices with Java 8 and data processing with Scala and Python together with Apache Spark)
Built microservices, jobs and tools:
Involved in growing the Java & Scala team with additional team lead responsibilities.
Client: Porsche AG
Client: Heinrich Schmid GmbH
Java Training on AWT, Swing, JCF, JDBC, Hibernate, Java Servlet API, JSP, Ant, Maven, JavaEE, EJB, JPA, JPQL, AOP with AspectJ, Glassfish, WSDL, SOAP, JAX-WS, JUnit, Mockito, JSF
Research & Development on Automatic UI Testing & Continuous Integration
Put in practice the possibilities offered by Selenium on automated GUI testing.
Mobile app with REST API in backend.
We've participated in Microsoft Imagine Cup - Games Competition in 2013 with "Team Impact" with a 3D game implemented in C# with XNA.
Based on a rich English bibliography on theoretical projections of technology.
I have attended several competitions in computer science and mathematics.
Alongside my interests in software engineering some of my other interests and hobbies are:
