Position: Data Quality Engineer for Thrasio
Company: Proxet
Experience required: 5y
English level: intermediate

Required skills

Job summary:

Our Data Analytics team is growing, we are seeking a Data Quality Engineer. Ideal candidate will have a passion for data quality and working with large data sets. The successful candidate will work to ensure the quality of the data and its collection.

Skills & Experience:

— Hands-on scripting experience using Python or similar scripting languages;
— Experience building and automating testing frameworks around data ingestion pipelines for master data management;
— Solid skills in writing and understanding SQL queries;
—Familiar with CI/CD principles and best practices in data processing;
— Еxperience in Data Validation, Data QA, Pipelines, ETL;
— Fluent written and spoken English.

As a plus

— Familiarity with data analysis tools like Great Expectations;
— Python data analysis libraries Pandas, NumPy, Pyodbc, Psycopg2;
— AWS services including S3, Redshift;
— Experience in Airflow.

We offer

— Challenging work in an international professional environment;
— The long-standing team as this is for a long term project;
— Competitive salary;
— Flexible work-from-home & remote work policy;
— Mastering the English language with a native speaker;
— 40-hour work week with flexible working hours;
— PE accounting and support;
— 20 paid vacation days per year;
— 14 paid sick days per year;
— Collaborative friendly team environment;
— Cozy fully equipped office space in the city center.

Responsibilities

— Perform hands-on testing of new pipelines and regression testing;
— Utilize Python and SQL to perform data quality control;
— Assist team in writing test documents test plan, test cases, and test summaries;
— Liaise with various groups including Data Analysts, Data Engineers, Product and Delivery Manager;
— Participate in the design process to better understand the project to ensure the team delivers;
— Investigate ETL workflows;
— Assist in defining new and refining existing processes and procedures;
— Create and execute automated verification scripts;
— Create reports, dashboards to provide insight into testing, test coverage and alerts;
— Design data quality checks and testing framework to investigate the data within the pipeline.