Senior Data Engineer (AWS, FiveTran, dbt, Snowflake)

Pay Transparency Salary Range: Not Available Application Deadline: 06/30/2026 Overview We are seeking a Data Solutions Engineer IV to design, develop, implement, and support data solutions across all lines of BOKF Financial. This role collaborates with engineers, architects, analytics partners, vendor partners, and functional leaders to define best practices, governance, and standards. The position mentors junior engineers and leads meetings as needed. Responsibilities Lead the design, implementation, and governance of enterprise ETL / ELT pipelines using Fivetran for managed ingestion and CDC, Snowflake as the central cloud data platform, and dbt for transformation, modeling, and analytics engineering. Design end‑to‑end data flows from source systems to curated, consumption‑ready datasets, covering source‑aligned raw ingestion, conformed and reusable transformation layers, and business‑ready data products optimized for analytics and reporting. Establish and enforce dbt engineering standards: develop modular dbt models (staging, intermediate, mart layers), reuse dbt macros for standardization, implement dbt tests, documentation, and lineage, and version‑control dbt projects aligned with enterprise release processes. Design and optimize Snowflake data architecture: warehouse sizing and workload isolation, partitioning, clustering, performance tuning, secure data sharing, access control models, and cost optimization. Define and drive Python, PySpark, and SQL standards for data engineering workloads, supporting advanced transformations, large‑scale processing, and streaming or hybrid use cases. Implement Infrastructure as Code (IaC) using Terraform to provision and manage Snowflake objects, cloud infrastructure, and supporting platform components in a repeatable and auditable manner. Design and integrate CI/CD pipelines for data engineering assets: automated deployment of dbt models, macros, and tests; environment promotion (dev → test → prod); code quality checks, linting, automated validation; controlled and traceable releases aligned with enterprise SDLC practices. Oversee and validate Fivetran connector configurations, schema evolution handling, and ingestion SLAs to ensure reliability and trust in source‑to‑target pipelines. Evaluate, approve, and govern open‑source and vendor data engineering tools (Fivetran, dbt, Snowflake, Kafka ecosystem, AWS services) with focus on scalability, security, maintainability, and cost efficiency. Lead proofs of concept and technical evaluations for new data engineering technologies and patterns, ensuring alignment with Snowflake‑centric, SQL‑first, and automation‑driven architecture principles. Establish best practices for pipeline observability, data quality, and operational monitoring, ensuring pipelines are robust, traceable, and production‑ready. Partner with platform, security, and compliance teams to ensure data pipelines, infrastructure, and deployments meet enterprise security, access control, and regulatory requirements without compromising developer productivity. Education & Experience Requirements This level of knowledge is usually acquired through a Bachelor's Degree in a data‑centric field (Computer Science, Economics, Information Systems, Data Analytics, etc.) and 7+ years of experience leading large‑scale data projects, or an equivalent combination of education and experience. Proven experience building, automating, and supporting solutions in large‑scale data ecosystems in production environments on‑premises or in Azure/AWS cloud service. Proven experience building highly complex and scalable data pipelines. Strong understanding of BOKF business information systems and Enterprise Data Warehouse concepts. Hands‑on experience designing, developing, and testing business intelligence & analytics solutions using proven or emerging technologies across multiple environments. Excellent oral and written communication skills to represent oneself and BOKF, and to present complex information clearly. Expert analytical skills to analyze complex problems with interrelationships and dependencies, identifying common themes and solutions. Ability to understand goals and build work plans to accomplish them, adjusting priorities as needed. Confidence representing Enterprise Data Solutions in meetings where business needs and use cases are presented, providing guidance with little oversight aligned with best practices and architectural principles. Strong sense of accountability, ownership of projects and responsibilities, and proactive issue resolution. Equal Opportunity Statement The companies in BOK Financial Corporation Group are equal opportunity employers. We are committed to providing equal employment opportunities for training, compensation, transfer, promotion, and other aspects of employment for all qualified applicants and employees without regard to sex, race, color, religion, national origin, age, disability, pregnancy status, sexual orientation, genetic information, or veteran status. Please contact View email address on click.appcast.io with any questions. #J-18808-Ljbffr BOK Financial