mkolarek
Data engineer with 10+ years of experience in various industries such as e-commerce, construction and property rights protection. Developing and maintaining ETL pipelines for analytics and ML, designing and implementing data platforms.
Technologies: Python, Scala, SQL, Apache Spark, Apache Kafka, PostgreSQL, MariaDB, MongoDB, Google BigQuery, RDF, SPARQL, Pandas, Django, Flask, AWS, Azure, Terraform, Docker, Kubernetes
Résumé/CV: https://markokolarek.com/pdf/Marko_Kolarek_CV.pdf
Email: [email protected]
Website: https://markokolarek.com/
LinkedIn: https://www.linkedin.com/in/mkolarek
Data engineer with 10 years of experience in various industries such as e-commerce, construction and property rights protection. Developing and maintaining ETL pipelines, designing and implementing data platforms.
Data engineer with 10 years of experience in various industries such as e-commerce, construction and property rights protection. Developing and maintaining ETL pipelines, designing and implementing data platforms.
Tech stack:
Data Engineering: Python, Scala, SQL, Apache Spark, Apache Kafka, PostgreSQL, MariaDB, MongoDB, Cassandra, Google BigQuery, EXASOL, RDF, SPARQL
Cloud: AWS, Azure
Ops: Docker, Kubernetes, Terraform
Email: [email protected] Website: https://markokolarek.com/ LinkedIn: https://www.linkedin.com/in/mkolarek
Data engineer with 10 years of experience in various industries such as e-commerce, construction and law. Developing and maintaining ETL pipelines, designing and implementing data platforms.
Tech stack:
Data Engineering: Python, Scala, SQL, Apache Spark, Apache Kafka, PostgreSQL, MariaDB, MongoDB, Cassandra, Google BigQuery, EXASOL, RDF, SPARQL
Cloud: AWS, Azure
Ops: Docker, Kubernetes, Terraform
Email: [email protected]
Website: https://mkolarek.github.io/
Data Engineer and Data Architect
Location: Worldwide
Languages: English (fluent), Croatian (native), German (basic)
Remote: Yes, hybrid possible in Germany
Willing to relocate: No
Technologies: Python (Flask, Django, pandas, scipy, Apache Spark), Scala (Apache Spark), IaaC (Terraform), AWS, MS Azure, DevOps (Jenkins, TravisCI, Gitlab CI/CD, MS Azure DevOps), Knowledge Graphs (RDF, rdf4j), Apache Kafka, OpenCV (C/C++, Python), relational databases (Postgres, MariaDB), noSQL (Cassandra, Mongo), monitoring/alerting (Grafana, Prometheus), platform tooling (Docker, Kubernetes, Helm Charts)
Personal website: https://mkolarek.github.io/
Résumé/CV: https://mkolarek.github.io/pdf/Resume-Marko-Kolarek.pdf
LinkedIn: https://www.linkedin.com/in/mkolarek
Email: [email protected]
Experience: 10 years of experience in data engineering
Looking for: both short- and long-term projects
Hi I'm Marko, a data engineer, data architect and consultant originally from Croatia, based in Berlin, Germany. I specialize in all kinds of data engineering work (ETL pipelines, data modelling, cloud infrastructure, cataloging, monitoring, MLOps, etc.).
Data Engineer and Data Architect
Location: Worldwide
Languages: English (fluent), Croatian (native), German (basic)
Remote: Yes, hybrid possible in Germany
Willing to relocate: No
Technologies: Python (Flask, Django, pandas, scipy, Apache Spark), Scala (Apache Spark), IaaC (Terraform), AWS, MS Azure, DevOps (Jenkins, TravisCI, Gitlab CI/CD, MS Azure DevOps), Knowledge Graphs (RDF, rdf4j), Apache Kafka, OpenCV (C/C++, Python), relational databases (Postgres, MariaDB), noSQL (Cassandra, Mongo), monitoring/alerting (Grafana, Prometheus), platform tooling (Docker, Kubernetes, Helm Charts)
Personal website: https://mkolarek.github.io/
Résumé/CV: https://mkolarek.github.io/resources/Resume-Marko-Kolarek.pd...
LinkedIn: https://www.linkedin.com/in/mkolarek
Email: [email protected]
Experience: 10 years of experience in data engineering
Looking for: both short- and long-term projects
Hi I'm Marko, a data engineer, data architect and consultant originally from Croatia, based in Berlin, Germany. I specialise in productionising and automating data projects, ensuring they can scale and reach their full potential.
I provide end-to-end support for all stages of a data product, from data analysis, design, prototyping, productionising, provisioning infra, deployment and operations.