Consultant, Data Engineer | Databricks

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 Consultant, Data Engineer will join the Altoids line within the Enterprise Data Office to support ITDM Modernization and the associated Enterprise Data Lakehouse (EDL) being created to enable it.

• Design and build Databricks and Delta Lake data pipelines that move ITDM data into reliable, reusable EDL layers.

• Develop Python and SQL transformations, data models, and data-quality checks that support IT demand, capacity, cost, and related reporting needs.

• Help establish scalable lakehouse patterns for ingestion, harmonization, curation, incremental processing, and downstream consumption.

• Partner with Altoids engineers, product managers, architects, analysts, and business stakeholders to translate ITDM needs into technical solutions and sprint-ready work.

• Troubleshoot pipeline, data-quality, and performance issues and contribute to monitoring, documentation, and production support.

• Create reusable engineering patterns and documentation that strengthen the EDL foundation and accelerate future ITDM delivery.

• At least 3+ years of strong hands-on experience with Databricks (, Delta Lake, Python, and SQL.

• Experience building and supporting enterprise data pipelines and lakehouse or data-platform solutions.

• Understanding of data quality, data modeling, performance optimization, and production operations.

• Ability to communicate clearly, work collaboratively in an Agile team, and turn complex data needs into maintainable solutions.

Success in this role means helping Altoids deliver a trusted, scalable Enterprise Data Lakehouse.

Work Authorization: This role does not qualify for employer-sponsored work authorization. Nationwide does not participate in the STEM OPT Extension program.

Work Arrangement: This role follows a hybrid schedule and requires in-office presence in our Columbus OH two days per week. Candidates must be based within a commutable distance to Columbus, Ohio.

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Job Description Summary

Nationwide’s industry leading workforce is passionate about creating data solutions that are secure, reliable and efficient in support of our mission to provide extraordinary care. Nationwide embraces an agile work environment and collaborative culture through the understanding of business processes, relationship entities and requirements using data analysis, quality, visualization, governance, engineering, robotic process automation, and machine learning to produce targeted data solutions.

If you have the drive and desire to be part of a future forward data enabled culture, we want to hear from you.

As a Data Engineer you’ll be responsible for acquiring, curating, and publishing data for analytical or operational uses. Data should be in a ready-to-use form that creates a single version of the truth across all data consumers, including business users, data scientists, and Technology. Ready-to-use data can be for both real time and batch data processes and may include unstructured data.

Successful data engineers have the skills typically required for the full lifecycle software engineering development from translating requirements into design, development, testing, deployment, and production maintenance tasks. You’ll have the opportunity to work with various technologies from big data, relational and SQL databases, unstructured data technology, and programming languages.

Job Description

Key Responsibilities:

• Consults on complex data product projects by analyzing moderate to complex end to end data product requirements and existing business processes to lead in the design, development and implementation of data products.

• Responsible for producing data building blocks, data models, and data flows for varying client demands…