Consultant, Data Engineer (Annuity Data Platform)

If you’re passionate about innovation and love working in an environment where you can constantly improve and adopt new technologies to drive business results, then Nationwide’s Information 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 will work a hybrid schedule coming into the Columbus, Ohio (preferred), Des Moines, Iowa, or Scottsdale, Arizona office 2 days (Wednesday & Thursday) per week.

Annuity Modernization team is looking for a highly experienced and technically proficient Consultant, Data Engineer to design, build, and optimize scalable data solutions across cloud and hybrid environments. This is a hands-on individual contributor role focused on engineering excellence, innovation, and delivering high-quality data products.

Key Responsibilities

• Implement robust data pipelines and lakehouse solutions using Snowflake and other cloud-native technologies.

• Develop and maintain ETL/ELT workflows using tools like Talend, Python ensuring performance, scalability, and reliability.

• Write and optimize complex SQL queries across multiple RDBMS platforms (Postgres, Oracle, SQL Server).

• Build containerized data applications using Kubernetes and cloud services (AWS).

• Design and manage data orchestration workflows using tools like UAC.

• Collaborate with data analysts, data testers and business stakeholders to understand data needs and deliver solutions.

• Ensure data quality, lineage, and observability across the data lifecycle.

• Contribute to technical standards, best practices, and reusable frameworks.

Required Qualifications

• 7+ years of hands-on experience in data engineering or related roles.

• Deep expertise in Snowflake platform, SQL, and ETL tools (Talend preferred).

• Strong programming skills in Python and/or Java.

• Experience with Kubernetes and containerized application development.

• Familiarity with cloud platforms (AWS).

• Proven ability to solve complex data problems and optimize performance.

• Excellent communication and collaboration skills.

Preferred Qualifications

• Experience in financial services, insurance, or other regulated industries.

• Knowledge of medallion architecture and data harmonization frameworks.

• Exposure to data governance, lineage tracking, and SLA monitoring.

#LI-AC1

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 such as dimensional data, standard and ad hoc reporting, data feeds, dashboard reporting, and data science resea