Consultant, Data Engineer | Snowflake Data Engineer (Python / Snowpark)

We need to output HTML fragment with sections: headings

for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections if posting has real specific content. We must not repeat job title as heading. Must not include Job ID etc. We need to extract content: The posting includes: - Intro paragraph about Nationwide dynamic organization etc. Could be "About the role" or maybe "About the role" is appropriate. - Work Arrangement: hybrid schedule, in-office presence two days per week, must be based within commutable distance to Columbus OH. That's schedule info. - Work Authorization: not qualify for employer-sponsored work authorization, no STEM OPT Extension. That's maybe not needed. - Role title: Snowflake Data Engineer (Python / Snowpark) – but we don't repeat as heading. - Then "Join the Finance & Investments Technology BSA..." This could be part of About the role. - Key Responsibilities list (bullets). Those are responsibilities. - Required Qualifications & Skills (list). That's qualifications/skills. - Job Description Summary (paragraph). Could be part of About the role or maybe separate. - Job Description Key Responsibilities: another long list of responsibilities (more detailed). Might duplicate earlier responsibilities but we need to preserve all substantive info; we can combine but not duplicate lines? The instruction: "Preserve ALL substantive information; do NOT invent or summarize away detail." We should keep both sets? Might be duplication but we can keep both as they are separate sections? However they are both responsibilities; we could merge but need to preserve all info; merging is okay as long as we don't lose detail. Safer to keep both but avoid duplicate identical lines. There's overlap but not exact duplicates. We'll include all bullet points from both sections. - Typical Skills And Experiences: education, experience, etc. That's qualifications. - Knowledge, Abilities and Skills: more skills. - Values: maybe not needed. - Benefits: list of benefits. - Compensation: salary ranges. - Overtime Eligibility: Exempt (Not Eligible) – maybe schedule? Not needed. - Working Conditions: Hybrid to normal office environment – schedule. - ADA statement: boilerplate, remove. - Note To Employment Agencies: boilerplate, remove. - Nationwide pays on geographic-specific salary structure... that's compensation detail. - Note on Compensation for Part-Time Roles: compensation detail. We need sections: About the role (intro + maybe work arrangement?), Responsibilities, Requirements/Qualifications/Skills (maybe combine), Benefits, Pay, Schedule. We must not create sections with filler like "commensurate with experience". We have actual content. Let's extract. **About the role**: Could combine introductory paragraph and the "Join the Finance & Investments Technology BSA..." plus maybe work arrangement? But schedule separate. We'll create:

About the role

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.

Join the Finance & Investments Technology BSA, a team focused on delivering innovative technology solutions that support Nationwide's finance and investment operations. This role offers the opportunity to influence enterprise-wide engineering standards, build reusable capabilities leveraged across multiple teams, and work with modern cloud and data technologies while partnering with architecture, security, governance, and product leaders.

**Responsibilities**: combine both Key Responsibilities and Job Description Key Responsibilities. We need to list as

• items. Let's extract bullet points from first Key Responsibilities: - Lead the design of enterprise-scale data warehousing and cloud integration strategies on Snowflake. - Establish standards for data ingestion, transformation, orchestration, and continuous performance tuning. - Build scalable ELT pipelines leveraging native Snowflake features like Snowpipe, Streams, Tasks, and Snowpark. - Implement data modeling frameworks (Dimensional, Data Vault, or hybrid schemas) using tools like dbt (data build tool). - Optimize query performance and manage warehouse compute costs through effective clustering, caching, and sizing. - Integrate orchestration tools (such as Apache Airflow or Prefect) to manage complex dependency graphs and scheduling. - Databricks, Apache Spark, PySpark, Apache Iceberg, Unity Catalog, or Snowflake/Databricks interoperability. (This seems like a bullet? It's a phrase; we can treat as bullet.) Now second list (Job Description Key Responsibilities) many sentences each ending with period. We'll break each sentence as bullet. List them: - Consults on complex data product projects by analyzing moderate to complex end-to-end data product requirements and existing business processes to lead 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 and exploration. - Translates business data stories into a technical story breakdown structure and work estimate so value and fit can be assessed 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 using 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 engineering using cloud technologies – Azure and AWS (i.e. Redshift, S3, EC2, Data-pipeline and other big data technologies). - Collaborates with the enterprise DevSecOps team and other internal organizations on CI/CD best practices experience and use of 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 business requirements and stories, creates and executes test data and scripts to validate that quality and completeness criteria are satisfied. Creates automated testing programs and reusable test data for future code changes. - Practices code management and integration with engineering Git principle and practice repositories. - Participates as an expert, leader, and learner in team tasks for data analysis, architecture, application design, coding, and testing practices. - Leads design decisions for complex data pipelines, integration patterns, and reusable engineering components within a product, platform, or domain. - May Perform Other Responsibilities As Assigned. - Reporting Relationships: Reports to Director or AVP Data Management leader. We could keep "May Perform Other Responsibilities As Assigned." and "Reporting Relationships:" as bullets. **Requirements / Qualifications / Skills**: combine Required Qualifications & Skills, Typical Skills And Experiences, Knowledge, Abilities and Skills. We need to avoid filler like "certifications are not required but encouraged" - that's okay. Let's extract: From Required Qualifications & Skills: - Experience: Strong experience in data engineering focused specifically on Snowflake architecture and implementation. - Technical Stack: Advanced SQL, Python (including PySpark or Snowpark), and modern transformation tooling like dbt. - Snowflake Expertise: Deep knowledge of Role-Based Access Control (RBAC), zero-copy cloning, time travel, and performance tuning. - Cloud Platforms: Hands-on experience within major cloud environments like AWS, Azure, or Google Cloud Platform (GCP). From 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: Six to ten 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, verbal 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. (Maybe we can include but it's values; could be separate but we can include as part of qualifications.) We could also include "Job Description Summary" paragraph as part of About the role. **Benefits**: list from Benefits section. Extract: - 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 - more (but "more" is vague; we can keep as "and more"). **Pay**: salary ranges. Extract: - The national salary range for Consultant, Data Engineer : $118,000.00-$222,000.00 - The expected starting salary range for Consultant, Data Engineer : $118,000.00 - $178,000.00 - Nationwide pays on a geographic-specific salary structure and placement within the actual starting salary range for this position will be determined by a number of factors including the skills, education, training, credentials and experience of the candidate; the scope, complexity and location of the role as well as the cost of labor in the market; and other conditions of employment. - If a Sales job, Sales Incentives, based on performance goals are possible in addition to this range. (Not sales role, but we can keep.) - Note on Compensation for Part-Time Roles: Please be aware that the salary ranges listed below reflect full-time compensation. Actual compensation may be prorated based on the number of hours worked relative to a full-time schedule. We'll include these as bullet points under Pay. **Schedule**: Work Arrangement and Working Conditions. Extract: - Work Arrangement: This role follows a hybrid schedule and requires in-office presence in our Columbus OH office location two days per week. Candidates must be based within a commutable distance to Columbus, Ohio. - Working Conditions: Hybrid to normal office environment. - Overtime Eligibility: Exempt (Not Eligible) (maybe include but it's not schedule; but we can include as schedule? Might be okay but it's not schedule; but we can include as part of schedule section? Might be better to include as schedule? The instruction: include Schedule section only if posting actually states them. It does state hybrid schedule and in-office presence two days per week. Also Working Conditions: Hybrid to normal office environment. Overtime eligibility is not schedule but we could still include but maybe better to keep schedule only. We'll include hybrid schedule and in-office requirement. We'll not include O