Data Analyst

WHO YOU ARE

o Bachelor's degree in Computer Science, Mathematics, related quantitative field, or equivalent practical experience;

o At least 5 years of work experience with Data Quality, BI/DWH testing; o Working knowledge of validation of dimensional models and facts/dimensions using SQL and Python;

o Knowledge in statistics tools (e.g., R, Python) is a plus;

o Experienced with BI and data visualization tools (e.g., Looker, Tableau etc.) is a plus; o Knowledge of methodologies Quality Assurance, as well as some tools and concepts (e.g., Data Governance, Data Profiling, Data Reconciliations and Data Quality measurement), are also a plus;

o An excellent strategic thinker with Data Quality mindset and with analytical skills. o Proven passion for the data quality discipline;

o An individual that can change directions quickly to respond to new information and changing circumstances;

o A team player, attentive to detail, good communicator both verbal and written and a problem solver; o Fluent in English.

WHAT YOU'LL DO

o Perform ad-hoc Data analysis to guide Data Quality improvement efforts; o Collect and compile statistics about the quality of our data;

o Prepare reports to communicate outcomes of quality activities;

o Conduct analyses and gather data; requirements specification, processing, and final data quality recommendations, collaborating with Data/Operational Engineering teams to implement checks to prevent issues and enhance quality on data the earliest possible;

o Create an automated process to identify issues and possible anomalies, and implement dashboards to measure KPIs and perform data validation;

o Support the definition of the Data Quality SLO’s for the company; o Build great relationships with your business stakeholders and other analytics teams - acting as a partner on analysing issues and bringing automated solutions for them; o Identify and champion improvements in our capability, such as data developments, best practices, and L&D;

o Contribute to the creation of quality assurance standards, policies and procedures to influence the Data Quality mindset across the company;

o Work in an agile fashion, and deliver on time and accurately.