Data Engineer

1 miesiąc temu


Kraków, Polska Verisk Pełny etat
Job Description

At Verisk Analytics we create sophisticated risk models to assist insurers with risk selection and pricing. Our range of models span residential and commercial property perils, motor insurance, travel, pet and health insurance. To feed our models we source diverse datasets covering high resolution weather data, property attributes, business activities and financial data, insurance data and geodemographic data. 


Role Purpose:
We are looking for a motivated individual with experience of developing ETL processes using AWS services and multiple database technologies. The role involves task management, ensuring the sourcing of data, dealing with 3rd parties and follow through the full data life cycle.
The role will rely on high levels of automation and a strong attention to detail to making sure that our processes flow smoothly and are effective. 


Role Responsibilities:

Ownership of the full data lifecycle, from sourcing to processing to delivery. Establish an ETL process for new datasets including full validation and data quality assessment.  Support, and operation of data processes. Work with the wider development team to improve the processes. Extraction of data for prospective customers to test models

Qualifications

University degree in information technology or similar At least 3 years of experience in a data management role including experience of developing ETL pipelines. Relational Database Management Systems (RDBMS) , SQL, NoSQL (DynamoDb, Redshift). Experience in defining data process improvement, defining requirements. General, overall knowledge of AWS Cloud services ( AWS Batch, Lambda, Step Functions, S3/Event). Data engineering and ETL pipeline building, Python and or .net programming or similar and interfacing with RDBMS  Experience with visualization tool (PowerBI/Tableau). Strong understanding of how to use automation to achieve processing scalability and speed. Experience working with data, including processes for data validation and quality control 

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