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.
We’re looking for a motivated Data Engineer – ETL Developer to join the NF Data Warehouse team within Digital Back Office(DBO). This role involves the delivery of data solutions and managing data integration across various Nationwide Financial products. This is a great opportunity to work on impactful data solutions that support a wide range of Nationwide Financial products, including Annuities, Life, Retirement, and Corporate Solutions.
In this role, you’ll help drive data integration efforts across platforms, working with a modern Snowflake-based data warehouse. You’ll be responsible for acquiring, curating, and publishing data for both analytical and operational use cases, while also helping to shape the future of our data ecosystem.

The ideal candidate will possess the following skills and experience:

• Proficient in SQL.
• Expertise in Snowflake is essential, familiarity with Oracle and SQL Server.
• Strong experience in ETL/ELT processes (Informatica/Talend).
• Solid understanding of data warehousing, data models, queries and batch processing.
• Experience working in Lean, Agile, DevOps, and Cloud hosting environments.
• Excellent collaboration and communication skills.
• Preferred experience in financial data management.

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.

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.

• 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.
  Reporting Relationships: Reports to Manager/Director Data Leader.