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

BOK Financial offers a senior data engineering leadership opportunity onsite in Richardson, TX, focused on building, governing, and optimizing enterprise data platforms. As a Senior Data Engineer, you will design and deploy scalable data solutions, collaborate with engineers, analytics partners, and platform teams, and mentor junior staff. This role requires a Bachelor’s degree and at least seven years of experience in data engineering, with a strong emphasis on maintainable, production-grade data pipelines.

Benefits

• Discretionary bonus

Responsibilities

• Lead the design, implementation, and governance of enterprise ETL and ELT pipelines, using Fivetran for managed ingestion and CDC, Snowflake as the central cloud data platform, and dbt for transformation, modeling, and analytics engineering.
• Architect and review end-to-end data flows from source systems to curated, consumption-ready datasets, including source-aligned raw ingestion, conformed transformation layers, and business-ready data products optimized for analytics and reporting.
• Establish and enforce dbt engineering standards, developing modular dbt models across staging, intermediate, and mart layers.
• Create and reuse dbt macros to standardize automation and consistency across projects.
• Implement dbt tests, documentation, and lineage to ensure data quality and transparency.
• Maintain version-controlled dbt projects aligned to enterprise release processes.
• Design and optimize Snowflake data architecture, including warehouse sizing, workload isolation, partitioning, clustering, and performance tuning.
• Develop secure data sharing and access control models and pursue cost optimization through efficient usage patterns.
• Define and drive Python, PySpark, and SQL standards for data engineering workloads, supporting advanced transformations and large-scale processing, including streaming or hybrid use cases where appropriate.
• Implement Infrastructure as Code with Terraform to provision and manage Snowflake objects, cloud infrastructure, and supporting platform components.
• Design and integrate CI/CD pipelines for data engineering assets, including automated deployment of dbt models, macros, and tests, with environment promotion across dev, test, and prod.
• Enforce code quality checks, linting, and automated validation; maintain controlled and traceable releases aligned with enterprise SDLC practices.
• Oversee and validate Fivetran connector configurations, schema evolution handling, and ingestion SLAs to ensure reliable pipelines.
• Evaluate and govern open-source and vendor tools (Fivetran, dbt, Snowflake, Kafka ecosystem, AWS services) for scalability, security, maintainability, and cost efficiency.
• Lead proofs of concept and technical evaluations for new data engineering technologies, ensuring alignment with Snowflake-centric, SQL-first, automation-driven architecture principles.
• Establish best practices for pipeline observability, data quality, and operational monitoring to keep pipelines robust and production-ready.
• Partner with platform, security, and compliance teams to ensure data pipelines and deployments meet enterprise security, access control, and regulatory requirements without hindering developer productivity.

Requirements

• Proven experience building, automating, and supporting solutions in a large-scale data ecosystem in production environments on-premises or in Azure/AWS.
• proven experience delivering highly complex and scalable data pipelines.
• Strong understanding of BOKF business information systems and Enterprise Data Warehouse concepts.
• Hands-on experience independently designing, developing, and testing business intelligence and analytics solutions across various technologies and environments.
• Excellent oral and written communication skills to clearly present information and issues.
• Analytical thinker with the ability to analyze complex problems and identify themes and solutions.
• Ability to translate goals into actionable work plans and adjust priorities as needed.
• Capable of representing the Enterprise Data Solutions team in meetings, providing guidance with minimal oversight and aligned to best practices and architectural principles.
• Strong sense of accountability and ownership, with proactive issue resolution.

Technologies

• AWS
• Fivetran
• dbt
• Snowflake
• Terraform
• Python
• PySpark
• SQL
• Kafka
• Azure