Lead Data Engineer
Arcitect & Design
Design and develop Snowflake-native data systems and architecture, including our medallion architecture. Supporting application ingestion, API connections, and advanced reporting needs across Finance, Risk, Lending, and Retail.
Pipeline Engineering
Build ETL/ELT pipelines for incremental and initial data loads into Snowflake using tools such as Matillion, Snowpipe, Dbt, Tasks, and Dynamic Tables, along with external orchestration tools, integrating data from core banking, loan origination, GL, and third-party systems.
Master Data & Governance
Define, build, and manage customer and customer product solutions by consolidating and mastering golden records with match & merge, survivorship, householding, and legal entity relationships. Establish data governance models, and enforce data quality, lineage, and consistency across systems. Align customer data models and hierarchies to support regulatory, operational, and analytical use cases.
Semantic Layer
Lead the design, development, and implementation of our enterprise-level semantic layer, building models that serve as the single source of truth for all bank reporting.
Performance Optimization
Optimize Snowflake warehouse utilization and SQL queries for maximum performance and cost efficiency and conduct performance tuning on reports and underlying data models.
Stakeholder Partnership
Partner with Finance, FP&A, Accounting, Marketing, and other areas to translate business requirements into scalable data models and KPIs, writing advanced SQL for complex financial transformations, reconciliations, and performance-critical queries.
Quality Control & Code Review
Conduct peer reviews, enforce data engineering standards, support CI/CD practices, improve documentation, and ensure data products meet agreed acceptance criteria before release.
Troubleshooting
Resolve complex pipeline, integration, reconciliation, and deployment issues across the warehouse, integration, and reporting stack, coordinating with source system owners and infrastructure partners as needed.
Observability
Implement monitoring, alerting, and data quality checks to ensure data timeliness, completeness, accuracy, and one version of the truth in destination systems.
Governance & Standards
Establish and enforce best practices around data modeling, version control, CI/CD, and documentation, and collaborate with Information Security, Infrastructure, Digital, and Risk to ensure SOX, GLBA, and other regulatory requirements are met.
Artificial intelligence
Support the bank’s responsible, coordinated, and value-driven adoption of AI by helping establish the data foundations needed for analytical and AI use cases and supporting multiple Bank AI use cases at one time.
Mentorship
Become a domain expert on our banking and financial services business and provide technical mentorship to other team members to foster a culture of continuous learning.