National Black MBA Association
Specialist, Data Engineer
National Black MBA Association, Raleigh, North Carolina, United States
Overview
Nationwide’s Technology team is looking for a hybrid Data Engineer who will support the Nationwide Financial Life Solution Area by providing data engineering capabilities for the ongoing support of the Life Data Lakehouse. The role is part of a highly motivated and exceptional team focused on delivering high quality outcomes in support of the Nationwide mission. Hybrid Work
This is a hybrid position with expectations to be in the Columbus, Ohio office 2 days a week on Wednesdays & Thursdays. Technical Skills
Proficiency in data engineering concepts, including data pipelines, data management, and data quality Experience with Extract, Transform, Load (ETL) processes and tools Strong programming skills, especially in Python and SQL Hands‑on experience with cloud platforms, particularly Amazon Web Services (AWS) Data modeling and data architecture expertise Familiarity with data governance and controls Knowledge of business intelligence (BI) tools and dashboard/reporting solutions Understanding of machine learning concepts and their application in data engineering Soft Skills
Strong communication skills, both written and verbal Critical thinking and problem‑solving abilities Agility and adaptability in a fast‑paced, collaborative environment Business acumen and the ability to translate business needs into technical solutions Innovation and continuous learning mindset Ability to work effectively within Agile methodologies Key Responsibilities
Provides technical consultation on data product projects by analyzing end‑to‑end data product requirements and existing business processes to lead in the design, development, and implementation of data products. Produces data building blocks, data models, and data flows for varying client demands such as dimensional data, standard and ad hoc reporting, data feeds, dashboard reporting, and data science research & exploration. Applies secure software and systems engineering practices throughout the delivery lifecycle to ensure data and technology solutions are protected from threats and vulnerabilities. Translates business data stories into a technical story breakdown structure and work estimate so value and fit for a schedule or sprint is determined. Creates simple to moderate business user access methods to structured and unstructured data by techniques such as mapping data to a common data model, NLP, transforming data as necessary to satisfy business rules, AI, statistical computations and validation of data content. Assists the enterprise DevSecOps team and other internal organizations on CI/CD best practices experience using JIRA, Jenkins, Confluence, etc. Implements production processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it. Develops and maintains scalable data pipelines for both streaming and batch requirements and builds out new API integrations to support continuing increases in data volume and complexity. Writes and performs data unit/integration tests for data quality. Practices code management and integration with engineering Git principles and practice repositories. Reporting Relationships
Reports to Manager/Director Data Leader. Education & Experience
Undergraduate studies in computer science, management information systems, business, statistics, math, a related field or comparable experience and education strongly preferred. Graduate studies in business, statistics, math, computer science or a related field are a plus. Three to five years of relevant experience with data quality rules, data management organization/standards, practices and software development. Experience in data warehousing, statistical analysis, data models, and queries. One to three years’ experience with Cloud technology and infrastructure including security and access management. Insurance/financial services industry knowledge a plus. Benefits
Medical/dental/vision, life insurance, short and long term disability coverage, paid time off, nine paid holidays, 8 hours of Lifetime paid time off, 8 hours of Unity Day paid time off, 401(k) with company match, company‑paid pension plan, business casual attire, and more. Equal Opportunity
Nationwide is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive culture where everyone feels challenged, appreciated, respected and engaged. Nationwide prohibits discrimination and harassment and affords equal employment opportunities to employees and applicants without regard to any characteristic (or classification) protected by applicable law.
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Nationwide’s Technology team is looking for a hybrid Data Engineer who will support the Nationwide Financial Life Solution Area by providing data engineering capabilities for the ongoing support of the Life Data Lakehouse. The role is part of a highly motivated and exceptional team focused on delivering high quality outcomes in support of the Nationwide mission. Hybrid Work
This is a hybrid position with expectations to be in the Columbus, Ohio office 2 days a week on Wednesdays & Thursdays. Technical Skills
Proficiency in data engineering concepts, including data pipelines, data management, and data quality Experience with Extract, Transform, Load (ETL) processes and tools Strong programming skills, especially in Python and SQL Hands‑on experience with cloud platforms, particularly Amazon Web Services (AWS) Data modeling and data architecture expertise Familiarity with data governance and controls Knowledge of business intelligence (BI) tools and dashboard/reporting solutions Understanding of machine learning concepts and their application in data engineering Soft Skills
Strong communication skills, both written and verbal Critical thinking and problem‑solving abilities Agility and adaptability in a fast‑paced, collaborative environment Business acumen and the ability to translate business needs into technical solutions Innovation and continuous learning mindset Ability to work effectively within Agile methodologies Key Responsibilities
Provides technical consultation on data product projects by analyzing end‑to‑end data product requirements and existing business processes to lead in the design, development, and implementation of data products. Produces data building blocks, data models, and data flows for varying client demands such as dimensional data, standard and ad hoc reporting, data feeds, dashboard reporting, and data science research & exploration. Applies secure software and systems engineering practices throughout the delivery lifecycle to ensure data and technology solutions are protected from threats and vulnerabilities. Translates business data stories into a technical story breakdown structure and work estimate so value and fit for a schedule or sprint is determined. Creates simple to moderate business user access methods to structured and unstructured data by techniques such as mapping data to a common data model, NLP, transforming data as necessary to satisfy business rules, AI, statistical computations and validation of data content. Assists the enterprise DevSecOps team and other internal organizations on CI/CD best practices experience using JIRA, Jenkins, Confluence, etc. Implements production processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it. Develops and maintains scalable data pipelines for both streaming and batch requirements and builds out new API integrations to support continuing increases in data volume and complexity. Writes and performs data unit/integration tests for data quality. Practices code management and integration with engineering Git principles and practice repositories. Reporting Relationships
Reports to Manager/Director Data Leader. Education & Experience
Undergraduate studies in computer science, management information systems, business, statistics, math, a related field or comparable experience and education strongly preferred. Graduate studies in business, statistics, math, computer science or a related field are a plus. Three to five years of relevant experience with data quality rules, data management organization/standards, practices and software development. Experience in data warehousing, statistical analysis, data models, and queries. One to three years’ experience with Cloud technology and infrastructure including security and access management. Insurance/financial services industry knowledge a plus. Benefits
Medical/dental/vision, life insurance, short and long term disability coverage, paid time off, nine paid holidays, 8 hours of Lifetime paid time off, 8 hours of Unity Day paid time off, 401(k) with company match, company‑paid pension plan, business casual attire, and more. Equal Opportunity
Nationwide is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive culture where everyone feels challenged, appreciated, respected and engaged. Nationwide prohibits discrimination and harassment and affords equal employment opportunities to employees and applicants without regard to any characteristic (or classification) protected by applicable law.
#J-18808-Ljbffr