As a team member in the Finance and Internal Audit department at Nationwide, the opportunities are endless! You can grow and learn in diverse areas across many disciplines such as Advanced Analytics, Investments, Actuarial, Accounting, Risk Management, Critical Business Advisor and so much more. Let Nationwide help create your career journey!As Data Engineer in the Property & Casualty data management team at Nationwide, you will be working with product manager and product owners to design, implement and scale data pipelines that transform data into actionable information and enables decision making. This role will be focused on supporting the Property and Casualty Telematics (IoT) line of business in partnership with advanced analytics team and the enterprise analytics office to design and build data pipelines based on business requirements.Ideal candidates will have the following skills:
- Experience programming in Python, Spark SQL, Dataframes and PySpark
- Experience with Spark architecture, big data concepts and building data lakes
- Experience with AWS S3, Glue, Kinesis or Kafka, EMR and familiar with Parquet and delta formats
- Experience with Databricks and Delta Lake
- Automate code deployment and promotion
- Diagnose and resolve technical issues or defects
- Design experience using best practices in building a data pipeline
- Experience in scrum team and working from business stories to task out and estimate work effort
- Experience leading a team of data engineers and provide mentorship
- Strong communication skills both verbal and written
- P&C Insurance and claims industry experience
Compensation Grade: F4Job 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 DescriptionKey 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.