Specialist, Data Engineer - India

If you’re passionate about being part of a dynamic organization that enables a Fortune 100 company with nearly $70 billion in annual sales to drive innovation and adopt new technologies that deliver business results, then Nationwide’s 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. Job Requirement 5-8 years' experience with data management, best practices and software development • 2+ years' experience with Databricks • Experience in Data Warehousing, data integration and data cleansing • Development of rules and mappings for data quality and accuracy • Strong experience in writing complex SQL • 2+ years' experience with Python • 3+ years of Cloud technology • Strong data troubleshooting skills - Oracle and MS SQL preferred • Strong teamwork and problem-solving skills • Experience with software development lifecycle • Experience with Agile / Scrum methodologies • Experience in Production issues and resolution • Experience with Perl a plus • Experience with AI Tools a plus Primary Skills - Python, AWS, SQL, Python. Good to have - Databricks/CICD pipeline, Pharos, GitHub. - 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: 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. Qualifications & Experience: 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. 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. Technical Skills: Amazon Web Services Data Engineering Data Management Data Pipelines Data Quality Extract Transform Load (ETL) Programming Skills Business Acumen Soft Skills & Attributes: Data application and practice knowledge Solid communication skills Ability to influence and set priorities Mentoring and coaching abilities to guide associates Identifying and removing blockers to progress Ability to work in agile and global environments Insurance/financial services industry knowledge a plus Other criteria, including leadership skills, competencies and experiences may take precedence Additional Information: Reporting Structure: Reports to Technology or Data Leader – India Working Hours: Aligned to India business hours with flexibility for global collaboration. Location Flexibility: [Hybrid/Remote/In-office] with periodic in-office collaboration. Equal Opportunity Statement: Nationwide is committed to diversity and inclusion. All qualified applicants will be considered without regard to race, gender, disability, religion, or other protected categories.