[Hiring] Senior Staff Data Architect @Infoblox

Role Description

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.

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.

Qualifications

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

Path to Success

• First 90 Days: Immerse in our culture, connect with mentors (Blox Buddies), and map the systems and meet with key stakeholders that rely on your work. Discuss and create short/long term goals.
• Six Months: Own and maintain at least two production data pipelines end-to-end, with documented SLAs, monitoring, and alerting in place. Deliver a measurable improvement to data quality or pipeline reliability against a baseline established in your first 30 days. Contribute dbt models or transformation logic that are peer-reviewed, tested, and certified for use by BI and analytics consumers. Build strong working relationships with cross-functional partners (Finance, Sales Ops, Customer Success) and demonstrate a clear understanding of their data needs.
• One Year: Be recognized as a reliable, high-quality contributor — pipelines you own run cleanly, documentation is current, and downstream consumers trust the data. Identify and drive at least one initiative that reduces technical debt, improves platform efficiency, or accelerates time-to-insight for a business stakeholder. Demonstrate growing fluency with AI-assisted development practices and contribute ideas for where automation or AI tooling can improve team productivity. Actively participate in code reviews and knowledge-sharing, raising the technical floor of the broader data engineering team.

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. Offers reflect role location, internal equity, experience, skills, education, and certifications. Base salary for this position: $150,000 - $210,000 plus bonus.