Sr Data Engineer Job Federal Way area,Washington USA,Software Development

Build and support enterprise-class data pipelines and scalable cloud data solutions in a hybrid role in Washington state.

Responsibilities

Design and develop complex multi-tier systems covering analysis, coding, testing, debugging, and documentation for cloud-native data solutions and integration services
Coordinate, support, and execute 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 align technical delivery with business needs
Support 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, and coordinate small to medium-sized teams through design reviews, code reviews, testing, 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 shaping and improving engineering best practices
Support monitoring and observability capabilities to improve pipeline performance, reliability, and operational outcomes
Use automation and AI-assisted development tools, including Git Hub 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 contribute to growing data engineering capabilities across the organization
Perform responsibilities in line with BECU Competencies, compliance, regulatory, and Information Protection requirements

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 coding experience with Python, Scala, Java, and SQL
Demonstrated experience with cloud technologies including Azure, AWS, and GCP
Demonstrated experience with modern data platforms including Azure Synapse, Azure Databricks, Redshift, Big Query, and Snowflake
Demonstrated experience with ETL/ELT, SQL, and cloud data integration tools, including Azure Data Factory, Azure SQL, Cosmos DB, Event Hubs, Azure Storage, Azure functions, Container apps, and API Management
Demonstrated experience with SQL, data modeling, data warehousing, data analysis, and supporting enterprise-scale operational data stores (ODS), data warehouses, and data lake or Lakehouse solutions
Experience with CI/CD systems and tools such as Azure Dev Ops and Git Hub
Experience with Git, including code reviews, pull requests, and branching standards such as Git Flow or Trunk-Based Development
Knowledge of financial services 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 Git Hub Copilot or AI-assisted Azure OpenAI, Azure AI Search, Copilot Studio, AI Foundry, MCP integrations, or related AI technologies
Previous experience with master data (MDM), metadata, data quality, data lineage, data cataloging, and data governance tools including Alation, Erwin, Collibra, Azure Purview, Infosphere, and Informatica MDM
Experience with Test Driven Development concepts, methods, and tools, including unit testing, integration testing, or performance/load testing
Proven ability to deliver highly scalable data solutions across the data lifecycle from ideation to retirement
Proven ability to stay current on emerging technologies and new applications of existing data technologies through work or continuing industry or education involvement
Proven experience leading and collaborating across teams and business units to deliver solutions through the SDLC
Experience presenting to technically adept audiences

Technologies

Python, Scala, Java, SQL
Azure, AWS, GCP
Azure Synapse, Azure Databricks, Redshift, Big Query, Snowflake
Azure Data Factory, Azure SQL, Cosmos DB, Event Hubs, Azure Storage, Azure functions, Container apps, API Management
Azure Dev Ops, Git Hub, Git
Git Flow, Trunk-Based Development
Git Hub Copilot, Azure OpenAI, Azure AI Search, Copilot Studio, AI…