Join a team, leading innovation at Nationwide in both analytical techniques and business capacities with many firsts at Nationwide.  An ideal candidate is passionate about both being technically advanced and delivering business solutions where you enjoy working directly with business users and managers, and receiving compliments for your results.

You will be working in an advanced analytics environment that is using the best technical products from streaming tools, Spark, Python, ML/AI tools, and Snowflake in AWS.  The business environment is that you will have opportunities to work in combined business and technical teams or user groups to focus on delivering business solutions with substantial value.  You will get to see the “fruits of your labor” with both business and IT leader feedback, and not feel that you are disconnected from seeing tangible results.

The role is a poly skilled role so you can wear many hats from data analyst, designer, coder, and tester in the data engineering role so you can deliver high-quality solutions with velocity.  You will work in an agile team with a data product owner and with business stories so you have a good understanding of the business value desired and have creativity and freedom to work with the business on how to design and build the business solution with some architectural guidelines.

A suitable background for this data engineering role is someone who is a current analytics solution builder with an IT background but may have also worked in a business department building analytical solutions directly for a business leader.  The technical background can be currently working as a big data engineer or even working on legacy technologies such as Hadoop, and other environments where strong SQL with a programming language skill has been developed.  Nationwide offers extensive training to advance your skills in DataBricks and Python classes to business training to advance your business/data expertise in a specific business domain like claims processing.  A $5K tuition reimbursement is also offered after one year so you can take university classes in AI, ML, or other areas of interest.

Multiple levels of job responsibilities for a big data engineer exist from junior, senior, and principal level roles are open.  The candidate will be joining a high-performing team that is passionate and motivated about meeting customer needs while also taking pride in its technical capabilities and delivery.  We also like to champion innovation by using new tools or capabilities to address a business requirement that has not been addressed in the past.   The team you will be joining is part of Nationwide’s Enterprise Data Office whose leader is the Chief Data Officer for Nationwide that is responsible for the analytics tooling and databases, technical accelerators, data governance, data strategy, data engineering, and data operations at Nationwide.

Nationwide currently has undertaken a massive analytics transformation program that will allow you to get in on the “ground floor” and become a key part of Nationwide’s analytical future.  You will have the opportunity to create new capabilities with little “legacy” or required enhancement of existing code. 

Compensation Grade: F4

Colorado Residents: Email taproces@nationwide.com for salary information

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: 

• 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

• 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.

Reporting Relationships: Reports to Manager/Director Data Leader.

Typical Skills and Experiences: 

Education:  Undergraduate studies in computer science, management information systems, business, statistics, math, a related field or comparable experience and education strongly preferred.  Graduate studies in business, statistics, math, computer science or a related field are a plus.

License/Certification/Designation:  Certifications are not required but encouraged.

Experience:  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. Insurance/financial services industry knowledge a plus.

Knowledge, Abilities and Skills:  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.

Other criteria, including leadership skills, competencies and experiences may take precedence.

Staffing exceptions to the above must be approved by the hiring manager’s leader and HR Business Partner.

Values:  Regularly and consistently demonstrates the Nationwide Values.

Job Conditions: 

Overtime Eligibility: Exempt (Not Eligible)

Working Conditions: Normal office environment.

ADA:  The above statements cover what are generally believed to be principal and essential functions of this job.  Specific circumstances may allow or require some people assigned to the job to perform a somewhat different combination of duties.