Engineering Director

Bridgenext Digital Engineering•,

3d•Remote

About The Position

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. 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.

Requirements

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
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

Nice To Haves

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

Responsibilities

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
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)
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
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
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
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