Data Quality Analyst (Temporary)

Monster Energy•Corona, CA

2d•$35 - $47

About The Position

In the position of Data Quality Analyst, you will be Responsible for implementing process improvements to increase the speed in which the data management team organizes and analyzes data. Ensure consistent, timely and accurate data the business can rely on for quality reporting when planning, forecasting, and doing other various data driven business decisions. Act as a subject matter expert (SME) on various business initiatives to provide guidance as necessary for data management and its governance. Please note: This is a Temporary position only.

Requirements

Bachelor's Degree in the field of Statistics, Computer Science, Business Administration or related field of study
Between 3-5 years of experience in in-depth analysis, using reporting tools and data sets
Proficient in Microsoft Office with highly developed skills in Excel. Proficiency in using spreadsheets to arrange, manipulate, format, and prepare large amounts of information.
Proficiency in Python, SQL and Power BI.
Highly effective analytical and problem-solving skills
Thorough understanding of Big Data Analytics and processes.

Responsibilities

Develop data quality and standards based on analytical research to avoid similar problems in the future. These standards will include building data validation procedures, quality checks and profiling reports.
Ensure adherence to regulatory requirements, data governance and documentation workflows.
Work with stakeholders and customers, 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.
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.
Analyze data quality issues, when problems with data integrity are discovered. Analyze and determine the root cause, working with other SMEs of the organization such as data stewards to understand how the data is collected, processed, and stored.
Validate data against business rules and industry standards. Verify data accuracy through cross-referencing.
Implement data validating procedures to ensure data integrity.
Identify data quality issues using a variety of tools and techniques such as data profiling and cleansing.
Work with other SMEs to develop metrics that can be used to measure the accuracy, completeness, and consistency of the data.
Monitor data quality, assessing and reviewing the data to ensure it meets the organization’s standards. Develop and run tests or use dashboards to track the health of the data.
Collaborate with other data professionals to ensure data quality is integrated across the entire data lifecycle, work closely with other professionals including data analysts and engineers.
Collaborate on data modelling and working with data architects to ensure 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.