Data Quality Engineer (R-15091)

Why We Work at Dun & Bradstreet Dun & Bradstreet harnesses the power of data through analytics, paving the way for a better future. Each day, we explore new ways to fortify our award-winning culture and speed up creativity, innovation, and growth. Our global team of over 6,000 members is passionate about what we do. We are committed to helping clients convert uncertainty into confidence, risk into opportunity, and potential into prosperity. We welcome bold and diverse thinkers. Come join us! About Us Our global group of colleagues bring diverse experiences and views to our work. We work from corporate offices and home desks alike, listening to our customers and crafting solutions. Our products and services are indispensable for companies of all sizes, scopes, and sectors. At the core of our work, you'll find our fundamental values: to be inspired by data, to be relentlessly curious and to be naturally generous. These values are the cornerstones of our evolving culture and guide how we work with each other every day! About the Role You will be part of the team tasked with overseeing the quality of our Global Inventory data. As a Data Quality Engineer, you play a pivotal role in maintaining our data quality, empowering our organization to make informed decisions and drive business success. This role entails working closely with cross-functional teams to ensure the accuracy, consistency, and dependability of our data assets. You will partner closely with stakeholders and other data engineers to construct data quality monitors, automate data quality processes, and propel ongoing enhancements. Key Responsibilities: - Craft a comprehensive data quality monitoring strategy that aligns with the organization's Data Quality Standards and business aims. - Develop a robust understanding of Dun & Bradstreet’s inventory data. - Undertake baseline data quality monitoring to proactively pinpoint data quality metric issues. - Use advanced data analysis and profiling techniques. - Automate data quality monitoring solutions and internal processes. - Work within data models that ensure data is stored in an organized structure. - Use PowerBI and/or Looker to design, create, connect, and manage dashboards that derive insights from data quality monitoring results. - Execute a robust data validation framework with automated testing processes. - Communicate with globally distributed stakeholders using JIRA and Confluence. - Accurately capture requirements and seek a deep understanding of use cases. - Suggest improvements to the data quality team’s internal processes. - Produce regular reports on data quality metrics. - Review data to identify patterns or trends that may indicate errors in processing. - Maintain comprehensive documentation of data quality processes and findings. - Adhere to data governance policies and procedures. - Educate yourself on industry best practices and technologies related to data quality. Required Traits Include: - Bachelor's degree in Computer Science, Information Technology, or a related field. - 2+ years of experience and demonstrated in-depth understanding of data analysis, querying languages, data modelling, and the software development life cycle. - Strong skill in SQL (preferably BigQuery). - An agile mindset and understanding of agile project management (Scrum/Kanban). - Understanding of Database design, modelling, and best practices. - Experience with cloud computing technologies (preferably GCP). - Experience with PowerBI, Looker or similar data visualisation tool. - Analytical, process improvement, and problem-solving abilities. - Good communication skills and the ability to articulate data issues and resolutions. - Commitment to meet deadlines and maintain the release schedule and exemplifying good teamwork to peers. Valuable Traits Include: - Skill in Python and/or Scala for data wrangling and data analysis. - Familiarity with DevOps best practices such as CI/CD, automation, monitoring, observability, agile project management, version control, and continuous feedback. - Experience with data observability tools like Acceldata or Informatica DQ. - Experience with XML and JSON data structures. - Understanding of ETL processes and their impact on data quality. - Knowledge of Machine Learning, specifically anomaly detection. - Experience working across time zones as part of a global team. What We’re Looking For: - Dynamic and results-focused team members with a focus on facilitating action and causing change. - An innovative and inspiring approach. - Self-motivation with a thirst for learning new techniques – relentless curiosity. - Ability to prioritize work with a flexible approach to juggling multiple tasks. - Ability to work independently. - A great team player. All Dun & Bradstreet job openings can be found at https://www.dnb.com/about-us/careers-and-people/joblistings.html. Official communication from Dun & Bradstreet will come from an email address ending in @dnb.com. Global Recruitment Privacy Notice