PAY RANGE

The Target Pay Range for this position is $141,800.00-$173,300.00 annually. The full Pay Range is $110,100.00 - $204,900.00 annually. At BECU, compensation decisions are determined using factors such as relevant job-related skills, experience, and education or training. Should an offer for employment be made, we will consider individual qualifications. In addition to your salary, compensation incentives are available for the hired applicant. Incentives are performance based and targets vary by role.

BENEFITS - because people helping people starts with supporting you

• 401(k) Company Match (up to 3%)
• 4% annual contribution to your 401(k) by BECU
• Medical, Dental and Vision (family contributions as well)
• PTO Program + Exchange Program
• Tuition Reimbursement Program
• BECU Cares volunteer time off + donation match

IMPACT YOU'LL MAKE:

The Senior Data Engineer is responsible for writing data workflows according to design specifications and completing complex development work. This role designs and codes features, automated tests, scripts, and data models while utilizing data management and governance tools. The position recommends and implements technical data products and solutions to address business needs, contributes to system architecture and design, and collaborates with technical leadership. Working closely with data engineers, business analysts, and systems analysts, the Sr Data Engineer builds and supports enterprise-class data solutions capabilities through high quality, resilient data pipelines and scalable cloud-based data solutions that enable business analytics, data governance, automation and operational reporting through and with emerging AI-driven capabilities.

WHAT YOU'LL DO:

• Design Enterprise Data Solutions: Design and develop complex, multi-tier systems including analysis, coding, testing, debugging, and documentation for cloud-native data solutions and integration services.
• Build Secure, Cost Effective, Scalable Data Pipelines: Coordinate, support, and execute the design and development of complex data workflows, including batch, near real-time, and API-based integrations.
• Drive Technical Innovation: Design and support prototypes, proofs of concept, and scalable data solutions that balance technical excellence with business needs.
• Champion Data Governance: Support and implement metadata management, master data policies, data quality standards, lineage, and governance practices within data workflows and pipelines.
• Enable Data Curation: Organize and guide data curation policies across data platforms and workflows based on technical requirements.
• Support and Mentor Data Engineering Teams: Support, mentor, organize, and coordinate small to medium-sized teams through design reviews, code reviews, testing efforts, and development activities.
• Collaborate on Technology Strategy: Partner with Architects, Product Owners, and leadership teams to document technology roadmaps, cloud modernization initiatives, and future-state data platform strategies.
• Elevate Engineering Excellence: Contribute to coding standards, CI/CD practices, automated testing, and code quality initiatives while helping define and improve engineering best practices.
• Enhance Reliability and Observability: Support monitoring and observability capabilities that improve visibility into pipeline performance, reliability, and operational outcomes.
• Leverage Modern Engineering Tools: Utilize automation and AI-assisted development tools, including GitHub Copilot and related technologies, to improve productivity and code quality.
• Partner Across Functions: Collaborate with architecture, governance, security, and platform engineering teams to deliver secure, scalable, reusable data products and services.
• Communicate Technical Expertise: Present technical topics to engineering audiences and help grow data engineering capabilities across the organization. Lead technical solution discussions, communicate recommendations and tradeoffs to technical and business stakeholders, and mentor engineers on solution design and implementation approaches.
• Ensure Compliance and Security: Perform all responsibilities in accordance with BECU Competencies, compliance, regulatory, and Information Protection requirements.

WHAT YOU'LL GAIN:

• The opportunity to influence the design and evolution of modern cloud-based data platforms at enterprise scale.
• Exposure to cutting-edge technologies across cloud, data engineering, automation, governance, and AI-enabled solutions.
• Opportunities to mentor and develop other engineers while contributing to a culture of technical excellence and continuous improvement
• Collaboration with cross-functional teams to deliver secure, scalable, and reusable data products that drive meaningful business outcomes
• The chance to build solutions that support analytics, operational decision-making, and future AI-driven data platform capabilities.

QUALIFICATIONS:

Minimum Qualifications:

• Bachelor's degree in computer science or related discipline, or equivalent work experience.
• Minimum 5 years of functional experience in data engineering.
• Minimum 4 years of experience in coding languages like Python, Scala, Java, SQL.
• Demonstrated experience using cloud technologies (platforms like Azure, AWS, GCP).
• Demonstrated experience using Modern data platforms ( Microsoft Fabric, Azure Databricks, Big Query, Snowflake).
• Demonstrated experience using ETL/ELT, SQL, and cloud data integration tools and Azure Services (Air Flow, Azure Data Factory, Azure SQL, Cosmos DB, Event Hubs, Azure Storage, Azure functions, Container apps, API Management.
• Demonstrated experience using SQL, data modeling, data warehousing, data analysis including designing, building and supporting enterprise scale operational data stores (ODS), data warehouses and data lake/ Lakehouse solutions.
• Experience using Continuous Integration and Continuous Delivery systems and tools such as Azure DevOps and GitHub.
• Experience using Git, performing code reviews, pull requests, and following branching standards such as Git Flow or Trunk-Based Development.
• Leading design discussions with team to elevate, empower and enable better design for long term solutions

Desired Qualifications:

• Knowledge of financial services industry concepts, regulations, and data domains, including banking, lending, deposits, payments, and risk management
• Experience building AI-ready data products and supporting AI agent architectures.
• Experience with using GitHub Copilot or AI-assisted Azure OpenAI, Azure AI Search, Copilot Studio, AI Foundry, MCP integrations, or related AI technologies.
• Previous experience in master data management (MDM), metadata, data quality, data lineage, impact analysis, data cataloging and data governance tools (Alation, Erwin, Collibra, Azure Purview, Infosphere, Informatica MDM.
• Experience in Test Driven Development concepts, methods, and tools. Demonstrated experience in unit testing, integration testing or performance/load testing.
• Proven ability to deliver highly scalable data solutions using a programming language compatible with the current technical environments over the entire data lifecycle (from ideation to retirement).
• Proven ability to stay current with emerging technologies and new applications of existing data technologies, through work or continuing industry or education involvement.
• Proven experience leading and collaborating within one or more teams, including business unit teams, to deliver solutions through all aspects of the SDLC and AI best practices
• Experience presenting in front of technically adept audiences.

JOIN THE JOURNEY:

Ready to make an impact? Join a team where your data engineering expertise can help drive cloud modernization, strengthen data governance, and enable the next generation of analytics and AI-powered solutions. You'll have the opportunity to solve complex challenges,