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!
The Enterprise Data Office (EDO) is seeking an energetic, innovative Analytics Data Engineer. This person is to work with IT, Business Leadership, and various Data Consumers in combining data from different sources that ensure efficient and effective delivery of data processes and projects within the Data Management area. The candidate will be joining a high-performing team that is passionate and motivated about meeting customer needs.
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We are looking for someone:
- Capable of influencing with and without authority
- General knowledge of Data Management, Data Quality, Data Lineage, Data Ops and DevOps
- Ability to learn new tools, technologies, and practices needed to address constant change in the technology landscape
- Capable of analyzing and driving the best data solutions for business partners
- Ability to mentor and develop other data professionals with a high degree of success
- Comfortable dealing with ambiguity
- Continuous improvement mindset
- Is an expert using Python and/or PySpark
- Experience using Agile methodology
- Experience with metadata-driven and fully parameterized programming methods
- Experience with streaming data
The experiences below would be considered a plus:
- Experience querying policy and quote data from Nationwide data sources
- Experience using Databricks
- Experience with the AWS ecosystem
Compensation Grade: G4
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:
Consults on complex data product projects by analyzing moderate to 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.
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.
Facilitates medium to 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, 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.
Participates as an expert and learner in team tasks for data analysis, architecture, application design, coding, and testing practices.
May perform other responsibilities as assigned.
Reporting Relationships: Reports to Director or AVP 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: Five to eight years of relevant experience with data quality rules, data management organization/standards and practices. Solid experience with software development on large and/or concurrent projects. Experience in data warehousing, statistical analysis, data models, and queries. One to three years’ experience with developing compelling stories and distinctive visualizations. Insurance/financial services industry knowledge a plus.
Knowledge, Abilities and Skills: Data application and practices knowledge. Advanced skills with modern programming and scripting languages (e.g., SQL, R, Python, Spark, UNIX Shell scripting, Perl, or Ruby). Strong problem solving, oral and written communication skills. Ability to influence, build relationships, negotiate and present to senior leaders.
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.