Data Platform Engineer

Farm Credit Services of America•Omaha, NE

About The Position

We are searching for a Data Platform Engineer to join our team. Our Data Platform Engineers design and scale the data backbone behind our enterprise analytics and AI initiatives, powering tools like Snowflake, Power BI, Alteryx, Salesforce, Qlik Replicate, Confluent Kafka, dbt and Boomi. In this high-impact role, you’ll build and maintain secure data platforms that enable high-performing data pipelines and integration that unify data across systems, enabling real-time insights and AI-driven solutions. Your work will accelerate smarter decision-making by ensuring reliable, governed, and accessible data across the organization. By optimizing data infrastructure and enabling self-service analytics, you’ll reduce reporting bottlenecks, boost operational efficiency, and unlock the full potential of data and AI for business innovation.

Requirements

Bachelor's degree in Computer Science & Software Engineering, Data Management & Governance, Cloud Computing & Infrastructure, Analytics & Business Intelligence or comparable experience in a related field required.
6+ years' of experience in Data Integration, Analytics, and Reporting platforms, Data Infrastructure, Data Development and governance.
Certifications in Microsoft Azure, Apache Kafka, and data integration technologies are highly valued.
Additional credentials in data and analytics platforms—such as Snowflake, Power BI, and similar tools—are considered a strong plus and demonstrate a well-rounded technical foundation.

Responsibilities

Design, build, and maintain scalable, secure, and AI-ready data platforms that deliver governed data assets across the enterprise.
Integrate with tools like Snowflake, Power BI, Alteryx, Kafka, and Boomi to unify data and enable real-time insights and self-service analytics.
Implement source control, CI/CD pipelines, and automation frameworks to streamline the development, deployment, and monitoring of data, analytics, and AI solutions—ensuring fast, reliable, and auditable delivery.
Enforce enterprise-grade data security practices including role-based access control, encryption, masking, and auditing to meet internal policies and regulatory requirements, while maintaining trust and transparency in data use.
Work cross-functionally with engineering, data science, reporting, and business teams to understand requirements, deliver scalable solutions, and drive innovation through data and AI.
Manage vendor relationships, software licensing, and contract renewals to align tools with organizational strategy.
Establish observability across data pipelines and platform usage, proactively resolving issues and ensuring performance.
Continuously monitor and optimize computer, storage, and licensing costs, while evaluating and integrating new features to evolve platform capabilities.