Director, Data Engineering

BECU•St. David's, WA

1d•$155,200 - $288,000•Hybrid

About The Position

The Director, Data Engineering, is responsible for leading the strategy, development, and operation of BECU’s Enterprise Data Platform (EDP), enabling scalable, secure, and governed data capabilities across the organization. This role owns the end-to-end data platform, spanning data ingestion, storage, processing, and consumption to support business intelligence, analytics, and AI/ML initiatives. The position partners closely with technology, analytics, and business leaders to drive data platform modernization, standardization, and innovation in a regulated environment, ensuring data is a trusted and strategic enterprise asset.

Requirements

Bachelor’s degree in computer science, Mathematics, related technical field or equivalent.
Minimum seven years of management experience leading technical individuals (data engineers, data scientists, data analytics, database administrators are ideal).
Minimum eight years of experience in data engineering, data science, programming and/or databases.
Experience working with data integration platforms; modern data and BI tools.
Knowledge and experience with iterative software development processes and continuous delivery.
Deep expertise in modern data engineering platforms including cloud data ecosystems (Azure/AWS/GCP), data lakes/lake houses, Enterprise data platform architectures, and both batch and real‑time data pipelines.
Experience with Data Governance, metadata management, data security, privacy and compliance.

Nice To Haves

Demonstrated business acumen and expertise contributing to roadmap and strategy discussions.
Client facing experience and ability to explain complex technical components or solutions.
Proven ability to lead and align teams to collaboratively achieve strategic goals and deliver measurable business outcomes
Experience working in an agile environment (Scrum and Kanban) with a cross functional team with the ability to manage multiple priorities.
Familiarity with data science and machine learning methodologies and use cases.
Experience working with business leaders and make strategic business decisions based on insights from operational data.
Experience leading and building data platforms that scale and in accordance with industry best practices.
Deep knowledge of industry best practices and standards to actively promote the effective and efficient use of Business Intelligence solutions to meet management objectives.
Hands‑on experience with data integration, modeling, and orchestration technologies, such as SQL/NoSQL databases, ETL/ELT frameworks, streaming platforms, and workflow tools.
Proven leadership in regulated or complex domains (financial services, banking, healthcare, or similar), with experience designing solutions that meet security, privacy, and compliance requirements.
Demonstrated experience in data platform modernization, including legacy system migration, cloud adoption, performance optimization, and observability/monitoring practices.
Solid understanding of AI/ML enablement for data platforms, including data quality, metadata management, governance, and support for analytics and AI use cases.
Relevant certifications preferred, such as cloud provider certifications (e.g., Azure Data Engineer, AWS Data Analytics).

Responsibilities

Lead & Inspire Teams: Build, mentor, and empower a high-performing team of data engineers and data professionals, fostering a culture of collaboration, innovation, and continuous growth.
Drive Data Platform Strategy: Lead the design and delivery of modern, scalable data platforms aligned with organizational goals and long-term vision.
Modernize the Data Ecosystem: Guide cloud adoption and legacy system migration, including Snowflake (or similar) implementation, ensuring minimal disruption and strong data integrity.
Build Scalable Data Pipelines: Oversee the design and operation of batch and real-time data pipelines using modern orchestration and engineering best practices.
Own the End-to-End Data Platform: Lead integration across data lakes, warehouses, and access layers to enable seamless data consumption for analytics and business use cases.
Advance Data Governance & Quality: Ensure strong data governance, metadata management, and adherence to security, privacy, and compliance standards.
Champion DevOps & DataOps: Drive adoption of modern engineering practices, including CI/CD, infrastructure as code, and containerization (Docker/Kubernetes).
Execute the Technical Roadmap: Translate leadership vision into actionable plans and deliver measurable outcomes against key business objectives.
Collaborate Across the Business: Partner with Data Science, Analytics, and business teams to align priorities and unlock the full value of data.
Establish Best Practices: Define and implement frameworks, standards, and processes that improve efficiency, scalability, and reliability.
Uphold Regulatory Excellence: Ensure all work meets BECU’s compliance, regulatory, and information protection requirements.
Develop Future Talent: Lead hiring, coaching, and career development efforts to grow strong and future-ready data organization.