As a Data Engineering Lead, you will leverage your expertise in Databricks, Python, SQL, and data pipeline knowledge, including PySpark, Pandas, and NumPy, to manage and optimize data workflows. Proficiency in AWS services such as S3, IAM, KMS, CodePipeline, and CloudFormation is essential. You will navigate and address ESS data and analytic needs with a DevOps/DevSecOps/DataOps mindset, ensuring adherence to best practices. Your role includes mentoring and training team members on design techniques, tools, and coding standards, fostering continuous learning and improvement through ongoing training, practice, and innovation. Additionally, you will collaborate with the Asset Suite Lead and Data Architect to ensure solutions align with design and coding standards and architectural guidelines. We are looking for someone who is eager and possesses a problem-solving mentality, thriving in a challenging environment.
Should be willing to work Arizona hours if not residing in Arizona.
Compensation grade G5
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.
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.
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.
Benefits
We have an array of benefits to fit your needs, including: medical/dental/vision, life insurance, short and long term disability coverage, paid time off with newly hired associates receiving a minimum of 18 days paid time off each full calendar year pro-rated quarterly based on hire date, nine paid holidays, 8 hours of Lifetime paid time off, 8 hours of Unity Day paid time off, 401(k) with company match, company-paid pension plan, business casual attire, and more. To learn more about the benefits we offer, click here.
Nationwide is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive culture where everyone feels challenged, appreciated, respected and engaged. Nationwide prohibits discrimination and harassment and affords equal employment opportunities to employees and applicants without regard to any characteristic (or classification) protected by applicable law.