Data Engineer - Snowflake & Activation Platforms

This is a remote position but applicant must live in Idaho, Utah, Montana, California, Nevada, or Oregon to qualify.

The Data Engineer is responsible for designing, building, and operating the downstream data layer that powers analytics, Salesforce enablement, marketing activation, lending insights, automation, and AI initiatives at Frontier Credit Union. This role owns the transformation, modeling, validation, and operationalization of data after it has been ingested into Snowflake. Upstream data sourcing, APIs, and ingestion pipelines are owned by a dedicated Software Engineering function.

This role partners closely with that team to define data contracts and ensure ingested data is production‑ready for downstream use. Activation platforms include Salesforce CRM, Salesforce Marketing Cloud, internal data applications, and AI‑enabled workflows. The focus of this role is ensuring data is trustworthy, well‑modeled, and usable by these systems.

• Serves as the primary owner of Snowflake‑based transformations and downstream data products.
• Translates raw ingested data into trusted, governed, analytics‑ready datasets.
• Ensures downstream consumers (Salesforce, Marketing Cloud, BI tools, internal apps, and automation workflows) receive consistent and reliable data.
• Identifies and resolves data quality issues arising post‑ingestion.
• Reduces downstream friction by enforcing standards, documentation, and observability across data layers.

• Design, build, and maintain Snowflake schemas, tables, views, and transformation layers.
• Implement scalable modeling patterns to support CRM, marketing, lending, and operational analytics.
• Write and optimize complex SQL transformations with a focus on correctness, performance, and cost efficiency.
• Maintain consistent metric definitions and reusable logic across business domains.

• Build and maintain transformation pipelines that convert ingested data into curated, business‑ready datasets.
• Implement dependency management, scheduling, and monitoring for downstream workflows.
• Support incremental processing, backfills, and reprocessing as business needs evolve.
• Partner with upstream engineers to define schema expectations, freshness SLAs, and data contracts.

• Prepare and maintain datasets that support Salesforce CRM and Salesforce Marketing Cloud use cases.
• Partner with Salesforce Administrators and Marketing teams to ensure downstream data supports segmentation, analytics, and reporting needs.
• Support identity resolution, deduplication logic, and business rules at the data layer.
• Ensure consistency between Snowflake‑curated data and downstream operational systems.

This role supports Salesforce through data products and pipelines, not platform administration or campaign execution.

• Implement data quality checks, validation rules, and anomaly detection for critical datasets.
• Monitor data freshness, volume, and schema stability for downstream tables.
• Build visibility into data readiness for analytics, automation, and operational use.
• Document data models, definitions, and ownership for key datasets.

• Build internal data tools and lightweight applications (e.g., Streamlit) to support operations, analytics, and decision‑making.
• Develop tools for pipeline health monitoring, data readiness checks, and operational reporting.
• Translate business questions into durable data products rather than one‑off analyses.

• Prepare feature‑ready datasets to support automation and AI initiatives.
• Partner with analytics and AI stakeholders to operationalize models and analytical outputs.
• Ensure downstream pipelines support reproducibility, auditability, and long‑term maintainability.

• Follow established development, testing, and deployment standards for data transformations.
• Use version control and documentation standards to support maintainability.
• Participate in incident…