PortfoLion Ventures is a venture capital and private equity organization. The company invests actively in small and medium enterprises of various industries.

- Designed and implemented a robust streaming data platform, leveraging Kafka and Terraform on AWS to support a self-service event-based architecture.- Developed multiple data pipelines to efficiently collect, process and integrate Ad tracking data from various sources into Snowflake and Snowflake data warehouse. Implemented custom pipelines using Meltano and deployed them to Kubernetes.- Created end-to-end user-tracking data platforms utilizing technologies such as Snowflake, BigQuery, dbt, Fivetran, Mixpanel, and Python.Key skills and tools:Snowflake, BigQuery, dbt, Fivetran, Hightouch, Redpanda, Python, Meltano, Kubernetes, Kafka, Terraform, AWS, GCP, Flink, Spark, Presto/Trino.

As a Google Cloud premier partner, I delivered end-to-end cloud-native data solutions for clients of any size; from startups to enterprises. Focus areas:- Data Warehouses, Lakes & Lakehouses - BigQuery, GCS, Datastore, Bigtable.- Streaming & Batch processing - Confluent Kafka, Dataflow, Dataproc (Spark), Presto/Trino, dbt- ETL/ELT Orchestration - Airflow- Infrastructure - Terraform, GKE- BI - Looker- MLOps - Kubeflow- CI/CD - Gitlab, Github Actions, Cloud Build

As team lead of the engineering squad, my main responsibilities were:• Taking ownership of the whole life cycle of our product and data, while enabling the engineering team behind it to reach its full potential.• Actively seeking out customer feedback to refine product roadmap.• Managing the technical needs and budgeting for a multinational expansion.

I helped build the tech stack behind Synetiq, which includes:- Custom-made software to record data from various biometric sensors (Eye tracking cameras, EEG headsets, etc.).- Fully automated, cloud-native ETL pipeline, consisting of hundreds of various data cleaning and aggregating steps, orchestrated by Luigi.- A data visualization dashboard application built with a modern web framework along with a cloud-based CI/CD solution.- Productionized algorithms developed by Data ScientistsEverything we built ran on GCP, mainly in a Kubernetes environment (GKE)

Main responsibilites:- Query building for recurring or Ad hoc reports.- Report automatization- Reporting and monitoring tool development- Front-end data visualization- Data mining using Oracle systems- ETL (extract, transform and load) task design and implementation.- RAN optimization support- Automated ZTE MML generation (GSM, UMTS, LTE) for RAN Operations- Radio network configuration managementTechnologies used:- Software development: Python, PHP, Perl, HTML5/CSS3/JavaScript - Database-related: MS SQL Server (Transact-SQL), Oracle (PL-SQL), MySQL