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You will serve as the primary owner of the company's emerging data platform, guiding its design and implementation in collaboration with stakeholders and partners. Additionally, you will be responsible for the ongoing operation, expansion, and governance of data pipelines and integrations to support business reporting and AI initiatives.
About Us:
EA Risk helps agricultural producers and the businesses that serve them manage commodity price risk. Our advisors work alongside dairy, cattle, swine and grain operations every day, combining brokerage, insurance, and advisory services with leading market intelligence. We take a fundamental, hands-on approach - our people are in the field and on the phone, not just behind a screen.
Formerly Ever.Ag Risk Management, we are now an independent company backed by Stone Point Capital, led by the same team that built the business.
About You:
You enjoy building data foundations that people can trust and use. You can help shape a new platform with an implementation partner, make sound technical decisions, and take responsibility for operating and improving it over time.
You already use AI tools substantially to accelerate development, investigate data, and learn unfamiliar systems. You pair that speed with careful validation and a strong understanding of data quality and access controls.
How the position fits in the organization
You will be EA Risk’s primary internal owner of our emerging data platform. Initially, you will work with the CTO, business stakeholders, and an external implementation partner to guide its design and build.
We expect to pursue a lakehouse approach using a platform such as Databricks. The architecture and technology choices remain open, and you will help evaluate what best meets the business’s needs.
You will then own the platform’s ongoing operation and expansion, supporting reporting, product capabilities, and governed use of enterprise data by AI tools. This is an individual contributor role.
Key contributions
Help define platform requirements, evaluate technology and architecture decisions, and guide the implementation partner’s work.
Build a clear path from partner delivery to sustainable internal ownership, including documentation and operational handover.
Develop and maintain integrations across business systems, product data, external providers, and public datasets.
Create reliable pipelines and well-defined datasets that support business reporting and application needs.
Establish monitoring, data quality checks, lineage, and processes for diagnosing and recovering from failures.
Work with business owners to resolve inconsistent definitions and reconcile records across systems.
Implement appropriate data access and governance in partnership with IT and security.
Extend the platform as new business requirements and acquisitions introduce additional data sources.
Use AI tools to accelerate engineering and investigation while validating transformations and outputs.
What you bring
Experience building and operating production data pipelines and modern data platforms.
Strong SQL skills and proficiency in a language used for data engineering, such as Python.
Practical understanding of data modeling, orchestration, testing, and cloud infrastructure.
The ability to evaluate technical proposals and work effectively with an external delivery partner.
An ownership mindset that includes ongoing reliability, usability, and operating costs.
Substantial current use of AI tools in your work.
Experience with lakehouse architectures or platforms such as Databricks is helpful. Familiarity with CRM, ERP, financial, insurance, or agricultural data is also valuable. We value demonstrated capability over a fixed experience threshold or particular degree.
Tools you will use
You will help select and develop a modern cloud data platform, likely using a lakehouse architecture. Data sources will include ERP and CRM systems, our customer-facing applications, external business partners, and public datasets.
Perks + Benefits
EA Risk is an Equal Employment Opportunity Employer. We are committed to providing equal employment opportunities to all qualified applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, veteran status, or any other status protected by applicable federal, state, or local law.
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