Data Quality Analyst

About Monster Energy :

Forget about blending in. That's not our style. We're the risk-takers, the trailblazers, the game-changers. We're not perfect, and we don't pretend to be. We're raw, unfiltered, and a bit unconventional. But our drive is unrivaled, just like our athletes. The power is in your hands to define what success looks like and where you want to take your career. It's not just about what we do, but about who we become along the way. We are much more than a brand here. We are a way of life, a mindset. Join us.

A day in the life :

Unleash your potential as a Data Quality Analyst at Monster Energy, where you'll supercharge our data management process! Be the ultimate speedster in organizing and analyzing data for flawless, timely, and reliable reports that drive our epic business decisions. You'll be the first line of defense, training data analysts on all things new and shiny. Craft killer training materials like MU courses and presentations, and dive into massive data sets with your razor-sharp critical thinking. Master our reporting and data systems, making game-changing recommendations with a focus on volume reporting and call point management. As the data champion, guide business initiatives and mentor a powerhouse team of analysts, making a legendary impact on Monster Energy's data journey!

The impact you'll make :

• Develop data quality and standards : These are based on analytical research to avoid similar problems in the future. These standards will include building data validation procedures, quality checks and profiling reports. Once created, it is their duty to ensure adherence to regulatory requirements, data governance and documentation workflows.
• Work with stakeholders and Customers : This could entail informing decision-makers about the implications of issues, working with data stewards to resolve data quality problems or creating educational resources to help other organization members and clients.
• Data Cleaning and Transformation : Extract, Transform and Load data. Cleanse and transform data to improve its quality and consistency. Implement data cleansing techniques such as standardization, normalization, and deduplication. Develop and execute data quality rules and scripts to automate data cleansing processes.
• Analyses data quality issues : When problems with data integrity are discovered the Data Quality Analyst will analyze and determine the root cause. This may involve working with other SMEs of the organization such as data stewards to understand how the data is collected, processed, and stored.
• Data Validation and verification : Validate data against business rules and industry standards. Verify data accuracy through cross-referencing. Implement data validating procedures to ensure data integrity.
• Identifying data quality issues : This entails using a variety of tools and techniques such as data profiling and cleansing. It is likely that they will work with other SMEs to develop metrics that can be used to measure the accuracy, completeness, and consistency of the data.
• Monitor data quality : This amounts to assessing and reviewing the data to ensure that it meets the organization’s standards. This may involve developing and running tests or using dashboards to track the health of the data.
• Collaborate with other data professionals : To ensure that data quality is integrated across the entire data lifecycle, it is necessary for them to work closely with other professionals including data analysts and engineers. This may involve collaborating on data modelling and working with data architects to ensure that the structure and quality is considered during the designing and implementation of systems.
• Create and distribute ad-hoc reports, standard reports, and dashboards based on requestor’s detailed requirements.
• Supports Leadership with ad-hoc assignments.

Who you are :

Monster Energy provides a competitive total compensation. This position has an estimated annual salary of $71,250 - $95,000. The actual pay may vary depending on your skills, qualifications, experience, and work location.