Specialist, Data Engineer - Snowflake and Python

Nationwide Mutual Insurance•Columbus, OH

1d•Hybrid

About The Position

The Data Engineer designs, builds, and supports scalable data pipelines and data products for analytics, reporting, operational insights, and AI-driven solutions across Nationwide Pet. The role partners with business teams, analytics, product owners, software engineers, and data scientists to deliver reliable, governed, high-quality data solutions in cloud and hybrid environments. The position acquires, curates, and publishes data in ready-to-use form for analytical and operational use, creating a consistent source of truth for business users, data scientists, and Technology. Data may support real-time or batch processes and may include unstructured data. The role contributes across the software engineering lifecycle, from translating requirements into design through development, testing, deployment, and production maintenance, and works with big data, relational and SQL databases, unstructured data technologies, and programming languages. The role follows a hybrid schedule, with in-office presence in Columbus, Ohio; Des Moines, Iowa; or Scottsdale, Arizona two days per week. Current remote associates will also be considered. Work hours support Nationwide Pet and Pacific Time Zone hours. The position does not qualify for employer-sponsored work authorization, and Nationwide does not participate in the STEM OPT Extension program.

Requirements

Four to six 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 of experience with cloud technology and infrastructure, including security and access management.
Moderate to advanced skills in modern programming and scripting languages, such as SQL, R, Python, Spark, UNIX shell scripting, Perl, or Ruby.
Knowledge of data applications and practices.
Good problem-solving and communication skills.
Required skills include Snowflake, Python, data warehousing and data modeling, AWS services, data pipeline development, API integrations, advanced SQL, Spark, CI/CD, and GitHub.
Experience architecting data solutions using modern platforms such as AWS, Snowflake, or Databricks.
Experience with AWS, APIs, and SaaS integrations.
Experience building and supporting batch pipelines, event-driven pipelines, API-based integrations, data ingestion frameworks, and data quality validation frameworks.
Experience enabling AI/ML and analytics use cases through scalable data platforms, data observability frameworks, monitoring tools, and Power BI reporting solutions.
Familiarity with data governance, metadata management, lineage, and security controls.
Experience monitoring, troubleshooting, and optimizing large-scale data pipelines.
Undergraduate studies in computer science, management information systems, business, statistics, math, a related field, or comparable experience and education are strongly preferred.
Certifications are not required.

Nice To Haves

Graduate studies in business, statistics, math, computer science, or a related field.
Insurance or financial services industry knowledge.
Certifications are encouraged but not required.

Responsibilities

Analyze end-to-end data product requirements and existing business processes, and lead the design, development, and implementation of data products.
Produce data building blocks, data models, and data flows for dimensional data, standard and ad hoc reporting, data feeds, dashboards, and data science research and exploration.
Apply secure software and systems engineering practices throughout the delivery lifecycle to protect data and technology solutions from threats and vulnerabilities.
Translate business data stories into technical work breakdowns and estimates to assess value and schedule or sprint fit.
Create business-user access methods for structured and unstructured data, using techniques such as common data models, NLP, data transformation, AI, statistical computations, and data-content validation.
Assist the enterprise DevSecOps team and other internal organizations with CI/CD best practices and tools such as JIRA, Jenkins, and Confluence.
Implement production processes and systems to monitor data quality and help ensure production data is accurate and available.
Develop and maintain scalable streaming and batch data pipelines and build API integrations to support increasing data volume and complexity.
Write and perform data unit and integration tests for data quality; create and execute test data and scripts to validate quality and completeness requirements.
Create automated testing programs and reusable test data for future code changes.
Follow engineering Git principles and practices for code management and integration.
Support delivery of data engineering solutions within a defined product or platform scope.
Perform other responsibilities as assigned.

Benefits

Medical, dental, and vision coverage.
Life insurance.
Short- and long-term disability coverage.
Paid time off, with newly hired associates receiving a minimum of 18 days per full calendar year, prorated quarterly based on hire date.
Nine paid holidays.
Eight hours of Lifetime paid time off.
Eight hours of Unity Day paid time off.
401(k) with company match.
Company-paid pension plan.
Business casual attire.