Specialist, Data Solution Analyst

Nationwide•Scottsdale, AZ

About The Position

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. As Nationwide’s Pet Insurance business grows, data is driving our next wave of innovation. From strategic decisions to customer insights, analytics are essential to our success. We’re seeking a skilled data professional to help evolve our Pet Data Warehouse into a scalable, intelligent platform that supports enterprise-wide transformation. This role supports the SEPM team across data and application domains, contributing to alignment and impact as we scale. It’s a chance to shape strategy, build future-ready solutions, and apply AI/ML-powered analytics to redefine pet insurance. 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.

Requirements

SQL & Python: Expert in SQL and knowledge of Python - advanced querying, data manipulation, and analysis.
Visualization Tools: Tableau, Power BI
Statistical Analysis: A/B testing, regression, clustering.
Cloud & Big Data: Snowflake, Oracle, Databricks.
Data Governance: Privacy laws (GDPR, CCPA), data security.
Data Modeling: Experience with data profiling mapping and modelling tools - conceptual/logical/physical models, normalization.
Database Systems: Relational (PostgreSQL)
ETL/ELT Tools: Informatica, Talend
Modeling Tools: Erwin
System Design: APIs, integration, scalability.
Ability to extend existing data model per enhancement requirements
Ability to lead requirements elicitation sessions and Elicits reporting and analytic requirements from business and technology requestors to generate visualization or analysis
Experience w/ Insurance domain data
Communication: Explaining insights to non-technical stakeholders.
Business Acumen: Aligning data work with strategic goals.
Problem Solving: Identifying patterns and proposing solutions.
Collaboration: Working across teams (engineering, product, execs).
Adaptability: Keeping up with evolving tools and trends.
Undergraduate studies in computer science, management information systems, business, statistics, math, a related field or comparable experience and education strongly preferred.
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.
Data application and practices knowledge.
Moderate to advanced skills with modern programming and scripting languages (e.g., SQL, R, Python, Spark, UNIX Shell scripting, Perl, or Ruby).
Good problem solving, oral and written communication skills.

Nice To Haves

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

Responsibilities

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 & 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 by such 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
With input from a business requirements/story, creates and executes testing data and scripts to validate that quality and completeness criteria are satisfied.
Can create automated testing programs and data that are re-usable for future code changes.
Practices code management and integration with engineering Git principle and practice repositories.
May perform other responsibilities as assigned.

Benefits

medical/dental/vision
life insurance
short and long term disability coverage
paid time off with newly hired associates receiving a minimum of 18 days paid time off each full calendar year pro-rated quarterly based on hire date
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