Remote Senior Enterprise Data Solutions Architect

Bridgenext

United States

Remote

USD 180,000 - 260,000

Full time

2 days ago

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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.