Consultant, Data Engineer - Reference Data Management

Nationwide is hiring a Consultant, Data Engineer focused on Reference Data Management, working in a hybrid environment in Columbus, OH. In this role, you will help configure and operate the Semarchy reference data management platform to support governed product and fund reference data, enabling trusted data access for downstream teams and applications.

Why this role

• Own technical implementation for data stewardship and governance, including governed views and APIs.
• Deliver approved reference data to Snowflake, the primary consumption path for downstream applications.
• Work across the full data lifecycle: design, integration, monitoring, reconciliation, and quality testing.
• Partner with business data owners and stewards to translate business decisions into models, rules, and workflows.

Responsibilities

• Partner with business data owners and stewards to translate reference data needs into Semarchy models, including product and fund entities, attributes, relationships, and hierarchies.
• Configure validation, match/merge rules, and authoring and approval workflows aligned to agreed business rules and stewardship practices.
• Recommend practical role and access patterns for people who create, review, and approve data, and support new domains and users adopting the platform.
• Build and operate data loads and integrations that bring product and fund reference data from source systems into Semarchy and deliver approved data to Snowflake, while supporting other required integrations.
• Maintain governed views and APIs that enable access without coupling consumers to Semarchy internal tables (for example, an application retrieving current, approved fund codes).
• Monitor pipelines, investigate failures, and reconcile records across sources, Semarchy, and destinations, including checks for accuracy, completeness, and timeliness.
• Break requirements into technical work, estimate delivery, and apply secure engineering practices as data flows and integrations are built and maintained.
• Document data definitions and identify critical data elements with data owners and stewards (for example, clarifying what a product or fund code represents and associated rules).
• Support quality profiling, lineage, metadata, and documentation so users understand origins, meaning, and usage of reference data.
• Embed governance standards in Semarchy workflows and quality checks, partnering with governance teams to address data issues and support adoption.
• Consult on complex data product projects by analyzing moderate to complex end-to-end data product requirements and existing business processes.
• Produce data building blocks, data models, and data flows for needs such as dimensional data, reporting, data feeds, dashboard reporting, and data science research and exploration.
• Apply secure software and systems engineering practices throughout the delivery lifecycle to protect data and technology solutions from threats and vulnerabilities.
• Create business user access methods to structured and unstructured data using mapping to common data models, NLP, transformations, AI/statistical computations, and validation.
• Build data cleansing, imputation, and standardization routines using data profiling and source data change monitoring, extraction, ingestion, and curation flows.
• Facilitate medium- to large-scale data engineering using cloud technologies including Azure and AWS (Redshift, S3, EC2, data pipeline and other big data technologies).
• Collaborate with the enterprise DevSecOps team on CI/CD best practices, using tools and platforms including JIRA, Jenkins, Confluence, and Git.
• Implement production processes to monitor data quality and ensure production data is accurate and available for key stakeholders and business processes.
• Develop and maintain scalable pipelines for streaming and batch requirements, and build new API integrations to support growth in data volume and complexity.
• Write and run data unit and integration tests for quality, creating test data and scripts to validate completeness and accuracy criteria, and building reusable automated test programs.
• Practice code management aligned with engineering Git repositories and participate in team tasks across analysis, architecture, design, coding, and testing.
• Lead design decisions for complex data pipelines, integration patterns, and reusable engineering components.

Requirements

• 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 (a plus).
• Six to ten years of relevant experience with data quality rules and 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.
• Advanced skills with modern programming and scripting languages, including SQL, R, Python, Spark, UNIX Shell scripting, Perl, or Ruby.
• Strong problem-solving and verbal and written communication skills.
• Ability to influence, build relationships, negotiate, and present to senior leaders.
• Certifications are not required but encouraged.
• Insurance/financial services industry knowledge (a plus).

Technologies

• Semarchy, Snowflake, SQL
• R, Python, Spark, UNIX Shell scripting, Perl, Ruby
• Azure, AWS, Redshift, S3, EC2, Data-pipeline
• NLP, AI
• JIRA, Jenkins, Confluence, Git

Benefits

• Medical/dental/vision
• Life insurance
• Short and long term disability coverage
• Paid time off (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

Job conditions

• Working Conditions: Hybrid to normal office environment.
• Overtime Eligibility: Exempt (Not Eligible).
• ADA: Statements cover principal and essential functions; specific circumstances may require some people assigned to the job to perform a somewhat different combination of duties.