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Engineering Director

Job in Phoenix, Maricopa County, Arizona, 85003, USA
Listing for: Bridgenext
Full Time position
Listed on 2026-07-31
Job specializations:
  • IT/Tech
    Data Engineering, Cloud Computing: Infrastructure & Operations
Salary/Wage Range or Industry Benchmark: 180000 - 280000 USD Yearly USD 180000.00 280000.00 YEAR
Job Description & How to Apply Below

Company Overview

Bridgenext is a digital consulting services leader that helps clients innovate with intention and realize their digital aspirations by creating digital products, experiences, and solutions around what real people need. Our global consulting and delivery teams facilitate highly strategic digital initiatives through digital product engineering, automation, data engineering, and infrastructure modernization services, while elevating brands through digital experience, creative content, and customer data analytics services.

Don't just work, thrive. At Bridgenext, you have an opportunity to make a real difference - driving tangible business value for clients, while simultaneously propelling your own career growth. Our flexible and inclusive work culture provides you with the autonomy, resources, and opportunities to succeed.

Position Description

We are seeking a highly experienced Engineering Director to be a Data Solutions Architect in our Global Data Practice and Engineering & Technology team. This role requires a hands‑on architect and leader with deep expertise in modern data platforms, enterprise, solution, and technical architecture, and data specialist technologies who can partner closely with customer stakeholders, sales, consulting, and delivery teams both internally and onsite with our clients.

The ideal candidate will bring a strong combination of enterprise data architecture experience and practical, field‑level expertise across cloud data platforms, enabling them to design, solution, and deliver scalable, business‑aligned data ecosystems.

This individual will support solutioning in both the pre‑sales phase and on select engagements, as well as provide architectural guidance and data engineering governance in support of modern implementation strategies across enterprise data initiatives including Data Lakes, Lakehouse platforms, Master Data Management (MDM), Data Governance, Data Migration, Analytics and Cloud‑native integrations.

Responsibilities include but are not limited to:

  • Enterprise Architecture & Data Platform Strategy
    • Define and evolve the enterprise data architecture vision, including conceptual, logical, and physical data models
    • Establish architecture standards for data platforms, integration patterns, data products, and domain‑driven architectures (Data Mesh/Data Fabric)
    • Act as the architecture authority for enterprise data initiatives, ensuring alignment with business goals and technology roadmaps
    • Design end‑to‑end data ecosystems spanning ingestion through consumption, across structured and unstructured data
  • Modern Data Platform Design
    • Apply deep expertise in field‑level data technologies, including Databricks, Snowflake, Microsoft Fabric, and cloud‑native services (Data Lakes, Warehouses, Lake houses)
    • Architect and implement modern cloud data platforms using Azure, AWS, and GCP
    • Design real‑time and batch data processing frameworks, including streaming architectures (Kafka, Event Hub, Kinesis)
      Optimize platform security, performance, scalability, and cost using hands‑on knowledge of distributed data systems and compute engines (Spark, Delta Lake, Iceberg)
  • Solution Architecture & Pre‑Sales Leadership
    • Partner with Sales and Solutioning teams to lead architecture‑driven pre‐sales efforts, including proposals, PoCs, and solution design
    • Translate complex business needs into architectural blueprints, reference architectures, and implementation roadmaps
    • Lead technical discussions with clients as a trusted advisor, bridging business and technology
  • Solution Delivery & Engineering Enablement
    • Own architecture for data pipelines, APIs, analytics platforms, and AI/ML‑ready data foundations
    • Guide engineering teams on best practices across data engineering, integration, and platform optimization
    • Ensure implementation of data governance, metadata, lineage, and quality frameworks across solutions
    • Provide hands‑on oversight in critical builds and escalations, demonstrating strong field‑level technical depth
  • Data Governance, Security & Compliance
    • Define enterprise standards for data governance, security, and privacy (PII, RBAC, encryption) to meet client specific needs and expectations
    • Ensure…
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