Sr Consultant, Data Engineer

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, Des Moines, Iowa or Scottsdale, Arizona office 2 days per week. Remote applicants will also be considered.

This role is within the Technology Property & Casualty Data Area.

Ideal candidate qualifications:

• Strong knowledge of python / spark with Databricks experience preferred.

• Understanding of DevOps practices and how they benefit data quality and integrity.

• Passion to discover creative new uses of AI to accelerate various efforts.

• Proactive and driven to use current technologies to help solve common problems.

• Strong communication skills with the ability to clearly and succinctly convey complex technical concepts to senior leadership.

#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 the most complex data product projects by analyzing 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 research & exploration.

• Translates business data stories into a technical story breakdown structure and work estimate so value and fit for a schedule or sprint.

• Responsible for applying secure software and systems engineering practices throughout the delivery lifecycle to ensure our data and technology solutions are protected from threats and vulnerabilities.

• Effective in team processes such as scrum, Kanban, and other agile processes, and communication of progress, blockers, and translation of the code being created to the story or business requirements. 

• Creates 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. 

• Builds data cleansing, imputation, and common data meaning and standardization routines from source systems by understanding business and source system data practices and by using data profiling and source data change monitoring, extraction, ingestion and curation data flows.

• Leads large-scale data using cloud technologies – Azure and AWS (i.e. Redshift, S3, EC2, Data-pipeline and other big data technologies).

• Collaborates with enterprise DevSecOps team and other internal organizations on CI/CD best practices experience using JIRA, Jenkins, Confl