Sr Data Engineer

BECU•Remote, WA, WA

14d•$110,100 - $204,900•Hybrid

About The Position

Is it surprising to hear that a financial institution of 1.5 million members and over $30 billion in managed assets say that success comes from focusing on people, not profits? Our “people helping people” philosophy has guided us since 1935, driving our deep commitment to serving our members, communities, and each other. When you join our team, you become part of a purpose-driven organization where your work makes a real difference. While we’re proud of our history, we’re even more excited about our future. With business and technology transformation on the horizon, there’s never been a better time to be part of BECU. You bring more than your expertise to your role, and that matters here. Your story, perspectives, and lived experiences help shape belonging at BECU and deepen how we connect with and support our employees, our members, and our communities.

Requirements

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 (Azure Synapse, Azure Databricks, Redshift, Big Query, Snowflake).
Demonstrated experience using ETL/ELT, SQL, and cloud data integration tools and Azure Services (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.

Nice To Haves

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 (MDM), metadata, data quality, data lineage, 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 required.
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 team, including business unit teams, to deliver solutions through all aspects of the SDLC.
Experience presenting in front of technically adept audiences.

Responsibilities

Design and develop complex, multi-tier systems including analysis, coding, testing, debugging, and documentation for cloud-native data solutions and integration services.
Coordinate, support, and execute the design and development of complex data workflows, including batch, near real-time, and API-based integrations.
Design and support prototypes, proofs of concept, and scalable data solutions that balance technical excellence with business needs.
Support and implement metadata management, master data policies, data quality standards, lineage, and governance practices within data workflows and pipelines.
Organize and guide data curation policies across data platforms and workflows based on technical requirements.
Support, mentor, organize, and coordinate small to medium-sized teams through design reviews, code reviews, testing efforts, and development activities.
Partner with Architects, Product Owners, and leadership teams to document technology roadmaps, cloud modernization initiatives, and future-state data platform strategies.
Contribute to coding standards, CI/CD practices, automated testing, and code quality initiatives while helping define and improve engineering best practices.
Support monitoring and observability capabilities that improve visibility into pipeline performance, reliability, and operational outcomes.
Utilize automation and AI-assisted development tools, including GitHub Copilot and related technologies, to improve productivity and code quality.
Collaborate with architecture, governance, security, and platform engineering teams to deliver secure, scalable, reusable data products and services.
Present technical topics to engineering audiences and help grow data engineering capabilities across the organization.
Perform all responsibilities in accordance with BECU Competencies, compliance, regulatory, and Information Protection requirements.