Senior Staff Data Architect

Infoblox • Olympia, WA

4d • $139,700 - $212,850 • Onsite

About The Position

We have an opportunity for a Senior Staff Data Architect to join our IT Data, Reporting & Analytics team in Home Office - NJ, reporting to the Senior Director, Data Analytics & Reporting - IT Executive. In this pivotal role, you will design, build, and maintain the scalable data pipelines and platform infrastructure that power Infoblox’s enterprise reporting, analytics, and AI-driven decision-making. Collaborating closely with Analytics Engineers, BI Developers, and cross-functional partners across Finance, Sales Operations, Customer Success, and IT, you will translate raw data from our enterprise application landscape into reliable, governed, and consumption-ready data products — and help elevate the maturity of a fast-growing data platform.

Requirements

• 10 plus years of professional experience in data engineering, analytics engineering, or a closely related discipline, with a track record of delivering production-grade pipelines and models
• Hands-on proficiency with SQL and Python; comfortable writing, reviewing, and debugging production code in both languages
• Practical experience with the modern data stack: cloud data warehouse (Databricks, Redshift, Snowflake, or equivalent), transformation frameworks (dbt or similar), orchestration (Airflow or equivalent), and ELT tooling (Fivetran, AWS Glue, or similar)
• Demonstrated experience building pipelines that ingest from SaaS enterprise applications (e.g., Salesforce, Oracle Fusion) via REST APIs, CDC, or batch patterns
• Working knowledge of data modeling concepts (dimensional, normalized, medallion/lakehouse) and the judgment to apply the right pattern for the right use case
• Familiarity with data governance fundamentals: RBAC, data lineage, metadata management, data quality frameworks, and access review processes
• Proven ability to work effectively in an Agile environment, manage competing priorities, and communicate clearly with technical and non-technical stakeholders
• BS/BA in Computer Science, Information Systems, Data Science, Engineering, or a related field; equivalent practical experience considered

Nice To Haves

• Experience with AI/ML-adjacent workflows — preparing datasets for ML consumption, using AI coding assistants, or implementing automated anomaly detection — is a plus

Responsibilities

• Build and maintain robust ELT/ETL pipelines ingesting data from enterprise source systems (e.g., Salesforce, Oracle Fusion, Marketo, Zuora) into the data lake and warehouse, ensuring reliability, freshness, and SLA adherence
• Develop and maintain data models across bronze, silver, and gold layers of the medallion architecture, applying dimensional, normalized, or data vault patterns as appropriate
• Implement data quality checks, automated monitoring, alerting, and logging so pipeline failures and anomalies are detected by the platform — not discovered by the business
• Maintain and improve the transformation layer using dbt (or equivalent), including model documentation, testing, lineage, and certification of data assets
• Enforce data governance standards: naming conventions, metadata, access controls (RBAC/CBAC), data masking, and retention policies aligned with security and compliance requirements
• Collaborate with Analytics Engineers and BI Developers to deliver consumption-ready semantic layer objects and reporting views that are accurate, performant, and reusable
• Leverage AI-assisted tooling (e.g., AI code assistants, automated anomaly detection, LLM-based documentation generation) to accelerate development, improve data quality, and reduce manual toil
• Participate in Agile sprint ceremonies, contribute to backlog refinement, and provide accurate effort estimates for data engineering work items
• Support evaluation and adoption of new tools and patterns in the modern data stack, providing evidence-based input on build/buy/adopt decisions
• Contribute to a culture of engineering excellence by writing clean, well-documented, testable code and participating in peer code reviews

Benefits

• Comprehensive health coverage, generous PTO, and flexible work options
• Learning opportunities, career-mobility programs, and leadership workshops
• Sixteen paid volunteer hours each year, global employee resource groups, and a “No Jerks” policy that keeps collaboration healthy
• Modern offices with EV charging, healthy snacks (and the occasional cupcake), plus hackathons, game nights, and culture celebrations
• Charitable Giving Program supported by Company Match
• We practice pay transparency and reward performance.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior