Oskar RYNKIEWICZ

Data Engineer and Data Scientist

Oskar is an all-round engineer with data science and software development skills. He takes interest in Big Data and has an aptitude for Machine Learning. Lately, he has been focused on harnessing Spark, Hadoop, and distributed systems. Over last 2 years, he acquired fluency in Python Data Science ecosystem tools. Having done 6 months internship as Research Engineer in a top university in Australia, he has the ability to address problems formulated with mathematics.

He obtained his diploma from the French school of engineering IMT Atlantique, with specialization in Information Processing Systems. He has been studying Computer Science and Statistics, participating in numerous projects and collaborating with people from various nationalities and backgrounds. Three years outside his home country, Poland, allowed him to obtain a broad perspective and competencies in French and English. He is a generalist with a diverse skill set, always keen on learning and pushing his technical abilities.

Published articles

Machine Learning model deployment

Machine Learning model deployment

Categories: Big Data, Data Engineering, Data Science, DevOps & SRE | Tags: AI, Cloud, DevOps, Machine Learning, On-premise, Operation, Schema

“Enterprise Machine Learning requires looking at the big picture … from a data engineering and a data platform perspective,” lectured Justin Norman during the talk on the deployment of Machine…

By Oskar RYNKIEWICZ

Sep 30, 2019

Spark Streaming part 4: clustering with Spark MLlib

Spark Streaming part 4: clustering with Spark MLlib

Categories: Data Engineering, Data Science, Learning | Tags: Spark, Apache Spark Streaming, Big Data, Clustering, Machine Learning, Scala, Streaming

Spark MLlib is an Apache’s Spark library offering scalable implementations of various supervised and unsupervised Machine Learning algorithms. Thus, Spark framework can serve as a platform for…

By Oskar RYNKIEWICZ

Jul 11, 2019

Spark Streaming part 3: DevOps, tools and tests for Spark applications

Spark Streaming part 3: DevOps, tools and tests for Spark applications

Categories: Big Data, Data Engineering, DevOps & SRE | Tags: Spark, Apache Spark Streaming, DevOps, Learning and tutorial

Whenever services are unavailable, businesses experience large financial losses. Spark Streaming applications can break, like any other software application. A streaming application operates on data…

By Oskar RYNKIEWICZ

Jun 19, 2019

Spark Streaming part 2: run Spark Structured Streaming pipelines in Hadoop

Spark Streaming part 2: run Spark Structured Streaming pipelines in Hadoop

Categories: Data Engineering, Learning | Tags: Spark, Apache Spark Streaming, Big Data, File Format, Data Governance, Python, Streaming, Hadoop

Spark can process streaming data on a multi-node Hadoop cluster relying on HDFS for the storage and YARN for the scheduling of jobs. Thus, Spark Structured Streaming integrates well with Big Data…

By Oskar RYNKIEWICZ

May 28, 2019

Spark Streaming part 1: build data pipelines with Spark Structured Streaming

Spark Streaming part 1: build data pipelines with Spark Structured Streaming

Categories: Data Engineering, Learning | Tags: Kafka, Spark, Apache Spark Streaming, Big Data, Streaming

Spark Structured Streaming is a new engine introduced with Apache Spark 2 used for processing streaming data. It is built on top of the existing Spark SQL engine and the Spark DataFrame. The…

By Oskar RYNKIEWICZ

Apr 18, 2019

Publish Spark SQL DataFrame and RDD with Spark Thrift Server

Publish Spark SQL DataFrame and RDD with Spark Thrift Server

Categories: Data Engineering | Tags: Hive, Spark, Thrift, JDBC, Hadoop, SQL

The distributed and in-memory nature of the Spark engine makes it an excellent candidate to expose data to clients which expect low latencies. Dashboards, notebooks, BI studios, KPIs-based reports…

By Oskar RYNKIEWICZ

Mar 25, 2019

Canada - Morocco - France

International locations

10 rue de la Kasbah
2393 Rabbat
Canada

We are a team of Open Source enthusiasts doing consulting in Big Data, Cloud, DevOps, Data Engineering, Data Science…

We provide our customers with accurate insights on how to leverage technologies to convert their use cases to projects in production, how to reduce their costs and increase the time to market.

If you enjoy reading our publications and have an interest in what we do, contact us and we will be thrilled to cooperate with you.