Westlake Corporation

The Data Quality Engineer is a critical role within our Data Governance team, you will work closely with functional Subject Matter Experts (SMEs) and report to the Manager of Data Stewards.. Thorough knowledge of data governance framework including data warehouse, metadata management, data quality, reference data/master data, data quality and data modeling. and their integration in enterprise systems (i.e. SAP, SFDC, JDE, Snowflake, Oracle, etc).. Proficiency programming and leveraging data quality tools (i.e. SAP Information Steward, BODS, USPS, Dunn and Bradstreet) to support enterprise initiatives.. A good understanding of data governance concepts, such as data ownership, data privacy, and data security, is required to ensure compliance with regulations and standards.

quality engineer

SUMMARYThe Data Quality Engineer is a critical role within our Data Governance team, you will work closely with functional Subject Matter Experts (SMEs) and report to the Manager of Data Stewards. You will implement data quality capabilities and processes to mature the data quality practice at Westlake. The ideal candidate will have a proven track record of implementing a first-generation data quality approach across master data domains using both third party and core application tool stack. You will be expected to lead conversations on how to improve the data lifecycle for Master Data Objects as well as facilitate the resolution of data quality issues through a Data Stewardship Council model. You will be viewed as the “go to” for the organization on data quality best practices. This role requires a high level of technical expertise, great attention to detail, and strong communication skills to work together with all global business stakeholders.DUTIES AND RESPONSIBILITIESMay include, but are not limited to, the following:<ul><li>Create a Data Quality Playbook to standardize the roles & responsibilities of data stakeholders for executing source system remediation to drive data quality improvements.</li><li>Collaborates with Business Leads, IT, and IS to ensure effective data management throughout the organization.</li><li>Partner with Data Stewardship Manager and business SME’s to identify and iterate metrics to measure data quality and roll up to Executive Business Leaders.</li><li>Focus on six areas of master data domains: Finance, Product, Item, Customer, Account, and Vendor.</li><li>Build cleansing, standardization, enrichment and validation approaches for both functional and domain-specific data quality dimensions on master data.</li><li>Complete analysis on adherence to the defined schema, data volume, data anomalies, expected distribution of datapoints in a dataset.</li><li>Monitor data quality metrics and perform root cause analysis of data quality issues that lead to data downtime, and take appropriate steps to address these issues with stakeholders.</li></ul>EDUCATION, EXPERIENCE AND QUALIFICATIONS<ul><li>Degree in Computer Science, Statistics, Business Administration, Computer Information, Data Science, or related area.</li><li>8+ years of related and progressive experience in Data Quality Management, Business Intelligence (BI), Data Analytics, and related fields.</li><li>Thorough knowledge of data governance framework including data warehouse, metadata management, data quality, reference data/master data, data quality and data modeling</li><li>Experience in managing master data domains (customer, supplier, item, finance, product, privacy, etc.) and their integration in enterprise systems (i.e. SAP, SFDC, JDE, Snowflake, Oracle, etc).</li><li>Excellent oral and written communication skills including the ability to effectively present technical topics to individuals and groups with potentially varied levels of technical sophistication.</li><li>Proficiency programming and leveraging data quality tools (i.e. SAP Information Steward, BODS, USPS, Dunn and Bradstreet) to support enterprise initiatives.</li><li>Proficiency data profiling, data mapping, and with data integration to establish data quality checks and resolving data quality issues (i.e. inconsistencies, inaccuracies, incompleteness in data products, etc).</li><li>Strong analytical skills to identify patterns, trends in data, and complete root-cause analysis to resolve data quality issues.</li><li>Proficiency in programming languages (i.e. SQL, Python) to help write and automate common functional DQ checks.</li><li>Excellent communication skills are required to collaborate with stakeholders, such as data analysts and data scientists.</li><li>A good understanding of data governance concepts, such as data ownership, data privacy, and data security, is required to ensure compliance with regulations and standards.</li><li>A mindset of continuous improvement</li></ul>PHYSICAL DEMANDS While performing the duties of this job, the employee is frequently required to sit; stand; walk; use hands to touch, handle, or feel; reach with hands and arms; and talk or hear. The employee is occasionally required to stoop, kneel, or crouch. The employee must regularly lift and/or move up to 5 pounds, frequently lift and/or move up to 10 pounds, and occasionally lift and/or move up to 15 pounds. Specific vision abilities required by this job include close vision, distance vision, color vision, peripheral vision, depth perception, and ability to adjust focus. Significant digital dexterity, e.g. using computer keyboard is required. Use of oral communication to perform work is required. WORK ENVIRONMENTThe noise level in the work environment is usually moderate as normally based in an open office concept. Some of the work may be required in the operating units which can require usage of required PPE including safety glasses, hearing protection, etc. May also result in exposure to outside elements and may require usage of stairs and elevators.

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