Principal Data Solutions Architect for Enterprise Data

Burtch Works

New York (NY)

Hybrid

USD 180,000 - 240,000

Full time

9 days ago

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Job summary

Burtch Works is seeking a Principal Solution Architect, Data to define, scale, and govern enterprise data architectures across multiple platforms and delivery teams. You will drive data products, modern data platforms, and AI-enabled capabilities to improve underwriting, enrollment, billing, claims, and analytics.

The role requires 15+ years of data architecture and solution delivery experience, cloud proficiency, and strong leadership.

Qualifications

Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field.
15+ years of experience in data integration, data architecture, data modeling, data engineering, solution architecture, or enterprise technology.
Proven experience designing and delivering enterprise-scale data platforms, data products, or analytics capabilities.
Strong understanding of modern data architecture principles, including data mesh, data products, metadata, governance, and domain-driven design.
Experience with modern data platforms such as Databricks, Apache Spark, Delta Lake, Kafka, or similar technologies.
Expertise in cloud platforms such as AWS, Azure, or GCP, APIs, microservices, and distributed systems.
Strong programming and data engineering skills in Python, PySpark, and SQL.
Experience rolling out AI capabilities or AI-enabled solutions within a data ecosystem.
Proven ability to define and drive adoption of architecture standards, frameworks, and reusable patterns.
Strong experience influencing technical direction across distributed teams without direct reporting authority.
Experience working in regulated or risk-sensitive environments with strong awareness of governance and compliance needs.
Exceptional communication, executive presence, and stakeholder management skills.
Experience collaborating within Agile and product-based delivery models.

Responsibilities

Own and shape enterprise solution architecture strategy, standards, and patterns across multiple platforms and domains.
Define and maintain reference architectures and reusable design patterns for solution delivery.
Establish architectural guardrails that enable scalable, secure, and consistent solution design across teams.
Lead enterprise-level design decisions for complex, high-impact initiatives that span multiple value streams or business units.
Provide architectural oversight and guidance across portfolios, ensuring alignment to enterprise standards and long-term strategy.
Drive early engagement on initiatives to identify cross-platform dependencies, systemic risks, and scalability constraints.
Partner with Enterprise Architecture and platform teams to define build vs. buy guidance and integration patterns.
Translate business and technology strategy into actionable architecture direction and solution designs.
Partner with Security, Risk, and Compliance teams to embed governance, security, and regulatory requirements into solution architecture.
Mentor and coach architects and senior engineers to elevate architectural maturity across the organization.
Represent solution architecture in enterprise forums, architecture review boards, and strategic technology discussions.
Drive the adoption of a data product operating model, championing customer-centric design, product ownership, continuous improvement, and measurable business value.
Establish best practices for discoverability, usability, interoperability, governance, and consumption of enterprise data products.
Lead discovery workshops and data solution design sessions across underwriting, enrollment, billing, claims, customer service, reporting, and digital channels.
Design modern data platforms and pipelines that support real-time and batch processing, scalable data integration, and enterprise analytics needs.
Ensure high-quality, trusted data through governance, observability, lineage, metadata, and automated data quality controls.
Collaborate with data engineering, product, and AI teams to operationalize AI-enabled data solutions within the data ecosystem.