Frontier Credit Union · 1 day ago
Data Engineer - Snowflake & Activation Platforms
Idaho Falls, ID
Full-time
Hybrid
Mid, Senior Level
3+ years expFrontier Credit Union is seeking a Data Engineer responsible for designing, building, and operating the downstream data layer that supports various analytics and marketing initiatives. The role involves collaborating with software engineers to ensure data readiness and quality for use in systems like Salesforce and AI workflows.
Financial ServicesNon ProfitWealth Management
Responsibilities
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
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 response related to downstream data failures
Continuously improve reliability, performance, and clarity of data products
Work closely with Software Engineers responsible for data ingestion and APIs
Collaborate with BI, Salesforce, Marketing, Lending, and Operations teams
Participate in requirements discovery, design reviews, and prioritization discussions
Communicate technical tradeoffs and constraints clearly to non-technical stakeholders
Qualification
Required
Advanced SQL skills, including complex transformations, window functions, and performance tuning
Strong Python experience for data pipelines, automation, and data tooling
Hands-on experience with Snowflake in production environments
Experience building downstream data pipelines and curated data layers
Familiarity with orchestration, scheduling, and transformation frameworks
Experience supporting downstream consumers such as BI tools, CRM platforms, or internal applications
Strong ownership mindset for data products
Ability to operate independently with clear accountability
Strong problem-solving and systems-thinking skills
Clear communication across technical and business audiences
Comfort working with sensitive data in regulated environments
Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent professional experience
3–6 years of experience in data engineering, analytics engineering, or a closely related role
Demonstrated experience building Snowflake-based transformations and data products
Strong production experience with SQL and Python
Preferred
Experience supporting Salesforce CRM or Salesforce Marketing Cloud as downstream consumers
Experience building internal data tools or applications (Streamlit preferred)
Experience in financial services or other regulated industries
Experience supporting automation or AI-driven analytics workflows
Company
Frontier Credit Union
Frontier Credit Union offers wealth management, online banking, and investment management solutions.
51-200 employees
Funding
Current Stage
Growth StageLeadership Team
Bob Hale
Chief Information Officer
Ethan M.
Chief Lending Officer
Recent News
2025-06-03
Company data provided by crunchbase