Specialist, Data Engineer

If you’re passionate about being part of a dynamic organization that enables a Fortune 100 company with nearly $70 billion in annual sales to drive innovation and adopt new technologies that deliver business results, then Nationwide’s Technology team could be the place for you! At Nationwide®, “on your side” goes beyond just words. Our customers are at the center of everything we do and we’re looking for associates who are passionate about delivering extraordinary care.

This role does not qualify for employer-sponsored work authorization. Nationwide does not participate in the Stem OPT Extension program.

• Design, build, and maintain data products and pipelines (batch and streaming) to support reporting, analytics, dashboards, data science, and operational processes.
• Acquire, transform, and integrate data from multiple internal and external sources, including structured, semi‑structured, and unstructured data.
• Develop data models and data flows (e.g., dimensional models, data building blocks) that align to business needs and enterprise standards.
• Translate business requirements into technical stories, estimates, and implementation plans for agile delivery teams.
• Implement and monitor data quality controls to ensure accuracy, completeness, and reliability of production data; create and run unit and integration tests for data solutions.
• Build and support APIs and data access methods to expose curated data to downstream consumers and applications.
• Apply Dev Sec Ops  practices, including use of CI/CD pipelines, version control, and automated testing, in line with enterprise standards.
• Partner with data architects, analysts, and business stakeholders to ensure solutions meet business objectives, data governance expectations, and security/privacy requirements.
• Provides basic to moderate 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 and exploration.
• Applies secure software and systems engineering practices throughout the delivery lifecycle to ensure our 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 using techniques such as mapping data to a common data model, NLP, transformation to satisfy business rules, AI, statistical computations and validation of data content.
• Assists the enterprise Dev Sec Ops  team and other internal organizations on CI/CD best practices 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; creates and executes testing data and scripts to validate that quality and completeness criteria are satisfied and can create automated testing programs and reusable data for future code changes.
• Practices code management and integration with engineering Git principles and practice repositories.

• Proficiency in SQL and at least one modern programming or scripting language such as Python and UNIX shell scripting.
• Experience with cloud data platforms and infrastructure (e.g., Snowflake, Databricks, or similar), including security and access management.
• Familiarity with ETL/ELT tools like Informatica, data pipelines, and orchestration frameworks.
• Working knowledge of modern data storage technologies (relational, dimensional, big data,…