Sr. Analyst, Data Engineer - India

About the job 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. Required Technical Skills – Data Engineer Candidates must possess a hands-on technical experience within the following technologies. These are foundational technologies within our tech stack that candidates will be working with on a daily basis in which competency is expected from the outset. ETL/ELT Pipelines using Informatica Powercenter/IICS/IDMC SQL, PL/SQL with Oracle and MS SQL Server, Snowflake Cloud Datawarehouse Amazon Web Services: EC2, S3, IAM, Lambda, EFS Python for Data processing using Pandas, dataframes, Numpy Github Version Repository AI Assisted Development: LLMs, RAG, embeddings, agents, prompt engineering Supplementary Technical Skills Particularly strong candidates would have exposure to the following additional tools and technologies. While familiarity in these are not strictly necessary from the outset, on-the-job upskilling will be required on a self-directed basis. Batch orchestration using UAC Stonebranch or similar (Autosys, Control-M, Airflow) Data-modeling, Star/Snowflake schemas and normalized designs. CI/CD: Harness, GitHub Actions, Jenkins Containerization & Orchestration: Docker, Kubernetes Monitoring & Observability: New Relic, Splunk, or similar tools 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. Key Responsibilities: Provides technical consultation on data product projects by analyzing end-to-end data product requirements and existing business processes to assist in the design, development and implementation of data products. Translates business data stories into a technical story breakdown structure and work estimate so value and fit for a schedule or sprint is determined. Applies secure software and systems engineering practices throughout the delivery lifecycle to ensure our data and technology solutions are protected from threats and vulnerabilities. Develops and maintains scalable data pipelines for both streaming and batch requirements. Assists in building out new API integrations to support continuing increases in data volume and complexity. Practices code management and integration with engineering Git principle and practice repositories. Qualifications & Experience May perform other responsibilities as assigned. 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 One to three years of relevant experience with data quality rules, data management organization/standards, or practices. Experience with query languages, statistical software and data wrangling and provisioning tools. Experience analysing trends and patterns in structured and unstructured data to support business problem solving. Technical Skills Amazon Web Services Data Engineering Data Management Data Pipelines Data Quality Extract Transform Load (ETL) Problem Solving Programming Skills Soft Skills & Attributes Data application and practice knowledge Effective communication skills Ability to set priorities 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.