Engineering Director

Bridgenext; United States; Remote; USD 180,000 - 260,000; Full time

Job summary

Bridgenext is seeking an Engineering Director to lead Data Solutions Architecture within our Global Data Practice and Engineering & Technology teams. This senior role combines hands-on architectural leadership with client-facing pre-sales and delivery oversight across cloud data platforms such as Databricks, Snowflake, and Microsoft Fabric.

You will guide enterprise data strategy, design scalable data ecosystems, and mentor data engineers and architects while collaborating with sales,

Qualifications

• 12+ years in data architecture, data engineering, or related roles, including 5+ years as a Solution/Data Architect.
• Proven experience defining and delivering enterprise-scale data architecture strategies.
• Strong understanding of architecture frameworks, cloud design patterns, and distributed systems.
• Deep hands-on expertise across modern data platforms including Azure, AWS and GCP (and related services).
• Strong experience with Databricks including Lakehouse architecture, Delta Lake, MLflow, Unity Catalog, Spark optimization.
• Experience with Microsoft Fabric including OneLake, Dataflows, Lakehouse, Notebooks, Semantic Models.
• Proven delivery of 2–3+ enterprise Data Lake/Lakehouse implementations.
• Expertise in ETL/ELT pipelines, batch and streaming architectures.
• Strong programming skills: SQL, Python, PySpark, Scala.
• Hands-on experience tuning Spark and distributed workloads.
• Strong understanding of IAM, RBAC, encryption, and secure data architectures.
• Experience with governance tools such as Azure Purview, AWS Glue Catalog, Unity Catalog.

Responsibilities

• Define and evolve the enterprise data architecture vision with conceptual, logical, and physical models.
• Set architecture standards for data platforms, data products, and Data Mesh/Data Fabric domains.
• Act as architecture authority for enterprise data initiatives, aligned to goals and roadmaps.
• Design end-to-end data ecosystems spanning ingestion to consumption across data types.
• Lead architecture-driven pre-sales, proposals, PoCs, and solution design.
• Translate complex business needs into architectural blueprints and roadmaps.
• Lead technical discussions with clients as a trusted advisor on data solutions.
• Own architecture for data pipelines, APIs, analytics platforms, and AI/ML-ready foundations.
• Guide engineering teams on best practices for data engineering, integration, and optimization.
• Ensure governance, metadata, lineage, and quality frameworks across solutions.
• Provide hands-on oversight in critical builds and escalations.

Skills

Enterprise data architecture

Solution/Data Architect

Enterprise-scale data architectures

Cloud design patterns

Distributed systems

Databricks

Lakehouse architecture

Delta Lake

MLflow

Unity Catalog

Spark optimization

Microsoft Fabric

Azure

AWS

GCP

Kafka / Event Hub / Kinesis

Data governance tools (Azure Purview /

Tools

Databricks

Snowflake

Microsoft Fabric

Azure

AWS

GCP

Kafka

Event Hub

Kinesis

Spark

Delta Lake

Iceberg

MLflow

Unity Catalog

OneLake

Dataflows

Notebooks

Semantic Models

Azure Purview

AWS Glue Catalog

Unity Catalog

Job description

At Bridgenext, we engineer Growth Operating Systems. Most enterprises have spent millions on their revenue stack and still aren't seeing the growth they expected. They have tools that function, but no system that wins. We help growth-hungry companies close that gap by turning fragmented platforms, siloed teams, and disconnected data into one integrated Growth OS. More than a technology company or marketing agency, we're a global digital consultancy with experts in engineering, data, AI, creative and more.

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

• 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, Lakehouses)
  • 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 compliance with regulatory frameworks such as GDPR, CCPA, HIPAA
  • Implement data lifecycle, retention, and auditability frameworks aligned with enterprise policies
• Leadership, Collaboration & Practice Building
  • Serve as a technical leader within the Data Practice, helping shape offerings, accelerators, and reusable assets
  • Mentor and coach data engineers, architects, and specialists on modern architecture and technologies
  • Collaborate across consulting, delivery, and client teams throughout the engagement lifecycle
  • Support contributions to RFP/RFI responses, including solution design and architecture artifacts

Workplace

This is a full‑time permanent position working remotely with up to 25–50% travel across the US.

Preferred Locations

Philadelphia, Boston, Atlanta and San Francisco but we are open to other US locations.

Must Have Skills

• 12+ years in data architecture, data engineering, or related roles, including 5+ years as a Solution/Data Architect
• Proven experience defining and delivering enterprise‑scale data architecture strategies
• Strong understanding of architecture frameworks, cloud design patterns, and distributed systems
• Deep hands‑on expertise across modern data platforms including Azure, AWS and GCP (and related services)
• Strong experience with Databricks including Lakehouse architecture, Delta Lake, MLflow, Unity Catalog, Spark optimization
• Experience with Microsoft Fabric including OneLake, Dataflows, Lakehouse, Notebooks, Semantic Models
• Proven delivery of 2–3+ enterprise Data Lake/Lakehouse implementations
• Expertise in ETL/ELT pipelines, batch and streaming architectures
• Strong programming skills: SQL, Python, PySpark, Scala
• Hands‑on experience tuning Spark and distributed workloads
• Strong understanding of IAM, RBAC, encryption, and secure data architectures
• Experience with governance tools such as Azure Purview, AWS Glue Catalog, Unity Catalog

Preferred Skills

• Experience in banking, financial services or Private Equity
• Experience in a highly consultative environment with clients
• Microsoft Certified: Azure Solutions Architect / Data Engineer Associate
• AWS Certified: Solutions Architect or Big Data Specialty
• Databricks Certified: Data Engineer or Architect
• Experience with hybrid and multi‑cloud environments
• Exposure to data product thinking, data mesh architectures, or domain‑oriented design
• Experience migrating large data volumes from legacy, on‑prem solutions to modern, cloud‑native environments

Professional Skills

• Excellent client‑facing communication and stakeholder management
• Strong ability to translate business needs into technical architecture
• Experience working in Agile and DevOps environments (CI/CD for data platforms)
• Demonstrated ability to operate as both a strategic architect and hands‑on data specialist

Bridgenext is an Equal Opportunity Employer

US citizens and those authorized to work in the US are encouraged to apply.