Nationwide's Information Technology team is looking to hire a Sr Consultant, Data Engineer to be an expert in building trusted data products using proper engineering practices, platforms, and architecture to drive business results and deliver extraordinary care to customers.
Requirements
- Expert level experience with cloud data platforms, frameworks, and lakehouse technologies (e.g. AWS, Databricks, Snowflake, Spark, Delta Lake/Iceberg).
- Hands-on building robust data pipelines using tools such as Spark, Talend, Informatica, or native solutions such as Delta Live Tables, or Snowpark. With experience implementing robust data quality and observability practices defines SLOs and data contracts, implements data validation, profiling, anomaly detection, lineage, and alerting.
- Strong software engineering in Python or similar. Applies TDD, modular design, and rigorous code reviews to produce maintainable, reusable components.
- Implements and matures DevOps practices for data. Builds automated testing, environment strategies, versioned data, and pipeline releases using infrastructure as code, and utilizes modern automated deployment patterns
- Advanced skills with modern programming and scripting languages (e.g., SQL, R, Python, Spark, UNIX Shell scripting, Perl, or Ruby).
- 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.
Responsibilities
- Consults on the most complex data product projects by analyzing 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.
- 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.
- Leads large-scale data using cloud technologies – Azure and AWS (i.e. Redshift, S3, EC2, Data-pipeline and other big data technologies).
- 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
Other
- Successful history of end-to-end data solution delivery, with first-hand experience scoping, sizing, and leading complex engineering initiatives, accountable for milestones, SLAs, and production outcomes.
- Demonstrated leadership and mentoring: uplifts team technical and soft skills, establishes engineering standards/patterns.
- Proven stakeholder communication skills to clearly convey status, risks, architecture decisions, and trade-offs to both technical and non-technical audiences; influences outcomes without formal authority.
- Effective in team processes such as scrum, Kanban, and other agile processes, and communication of progress, blockers, and translation of the code being created to the story or business requirements.
- Participate as leader, mentor and learner in team tasks for data analysis, architecture, application design, coding, and testing practices.
