Principal Data Engineer

Arvest Bank is seeking a Principal Data Engineer to lead the design and development of enterprise data platform solutions. The role involves mentoring data engineers, overseeing data architecture, and ensuring the quality and performance of data solutions.

Responsibilities:

• Serve as an SME while mentoring and providing solution oversight through the development of resilient data pipeline solutions
• Lead cross-team root cause analysis, troubleshoot highly complex problems and perform impact analysis of proposed changes
• Ensure quality of work delivered by the team meets standards for reusability, security, and performance and that data is available, usable, and fit for purpose
• Streamline the development and growth of data environments while proactively seeking opportunities for improvement
• Collaborate across the Enterprise to design solutions that meet business requirements and prove to be robust, stable, scalable, and adaptable over time
• Build solutions that are easily automated and allow for quick identification of failures
• Evaluate and optimize new integration patterns, frameworks, and third-party solutions by conducting research and developing proof-of-concept models. Influence the current and future state of technology by advocating technical difficulties experienced by the team
• Be an active leader in cross-product teams while promoting the re-use of data across the Company
• Lead code reviews and set code quality standards
• Understand and comply with bank policy, laws, regulations, and the bank's BSA/AML Program, as applicable to your job duties. This includes but is not limited to; complete compliance training and adhere to internal procedures and controls; report any known violations of compliance policy, laws, or regulations and report any suspicious customer and/or account activity

Requirements:

• Bachelor's Degree in Information Systems, Computer Science, Business Intelligence, or related field, or equivalent related work or military experience
• 8 years of experience in designing and developing data queries for ETL data movement, including merging large data sets for analysis
• 2 years of experience in designing, building, managing, and optimizing data environments for advanced analytics and data science
• Advanced knowledge in SQL (DBT required)
• Building complex data sets
• Feature engineering
• Data science lifecycle
• Enterprise ETL tools (DataFlow, Dataproc, Data Fusion, DataStage, Informatica, or similar)
• Fluency in Python, Java, Kafka, and C#
• Pipeline Orchestration of data workloads (Apache Airflow or Cloud Composer)
• Standardization, security, governance, and compliance
• MUST HAVE: Applied Agentic AI: Systems, Design & Impact
• MUST HAVE: GCP certification (could include Associate Cloud Engineer (ACE), or a specific path within the Professional Google Cloud offerings)
• CDMC: Certification: Cloud Data Management Capabilities (comprehensive best practices framework for cloud, multi-cloud, and hybrid-cloud environments)
• Lean Six Sigma
• COBIT 2019
• DCAM: Certification: Data Management Capability Assessment Model (Best practice for data management & analytics)
• CIMP: Certified Information Management Professional
• Cloud Technologies
• Data Visualization tools (Tableau, Looker, or PowerBI)
• Prior banking/financial services experience
• Certifications: AWS Certified Big Data – Specialty, Google Cloud Professional Data Engineer