Mikolaj Wilk

Mikolaj Wilk has a diverse work experience in various roles and industries. Mikolaj started their career as a Visitor Experience Associate at the New York Hall of Science in 2015. Later, they joined the NYU Tandon School of Engineering as an Engineering Research Associate, where they created and maintained workshop series on various topics and taught Python programming and data visualization. During their time there, they implemented data-driven strategies and marketing methods to significantly increase workshop attendance.

In 2020, Mikolaj transitioned to the role of a Python Automation Developer at S&P Dow Jones Indices, where they utilized their programming skills to automate processes. Mikolaj joined 1010data in 2021 as a Data Engineer, where they overhauled data pipelines, improved performance, implemented data retention policies, and enabled Airflow monitoring.

Throughout their career, Mikolaj has consistently demonstrated proficiency in programming languages like Python and familiarity with tools such as Apache Airflow, MatLab, R, and GitHub. Their experience and skills make him a valuable asset in data engineering and automation.

Mikolaj Wilk's education history includes attending the NYU Tandon School of Engineering in 2020 for a Bridge Program in Computer Science. In the same year, they also obtained the certification of AWS Certified Solutions Architect - Associate from Amazon Web Services (AWS).

In 2019, Mikolaj attended the NYC Data Science Academy for a 12-week in-person Data Science Bootcamp.

From 2009 to 2014, Mikolaj studied at Rutgers University and earned a Bachelor of Science (B.S.) degree in Physics.

Additionally, Mikolaj has obtained several certifications, including the Astronomer Certified DAG Authoring for Apache Airflow from Astronomer in 2022, the Google Cloud Certified Associate Cloud Engineer certification from Google in 2021, the Confluent Certified Developer for Apache Kafka from Confluent in 2022, and the Databricks Certified Associate Developer for Apache Spark 3.0 from Databricks in 2021.