Data Solutions Architect

Scope and Level of Influence

• Individual contributor role with enterprise‑level impact; leads through influence, not through direct reporting relationships.

• Serves as the recognized design authority for assigned data domains and initiatives, with the standing to approve, challenge, or redirect solution designs.

• Operates with a high degree of autonomy on ambiguous, cross‑domain problems where requirements, ownership, and precedent are not yet established.

• Sets direction that is adopted by multiple delivery teams and persists well beyond the life of any single project.

• Escalates and resolves architectural disagreements across teams, bringing stakeholders to a defensible, documented decision.

• Trusted to represent the data organization in enterprise forums, executive conversations, and vendor or partner discussions.

Key Responsibilities

Technical Leadership and Direction

• Set and communicate the technical direction for data solutions across assigned domains, establishing the patterns, standards, and reference designs that other teams build against.

• Serve as design authority for significant data initiatives—reviewing, approving, and where necessary challenging designs proposed by delivery teams.

• Drive alignment across teams with competing priorities, differing technical opinions, and separate reporting lines, building consensus where possible and making clear recommendations where consensus is not reachable.

• Make and defend architectural decisions under uncertainty, documenting rationale, trade‑offs, and the conditions under which a decision should be revisited.

• Anticipate downstream technical and organizational consequences of design choices, and proactively raise risks before they become delivery problems.

• Represent data architecture positions credibly to senior technology and business leadership.

Data and System Solution Design

• Design and implement end‑to‑end data solutions, including data warehouses, data lakes, and data pipelines, to support analytics, reporting, and AI initiatives.

• Define logical and physical data models that balance business usability with technical efficiency.

• Select and apply appropriate technologies (cloud platforms, database engines, orchestration tools) based on use case, scale, and cost considerations.

Business and Technical Translation

• Partner with business stakeholders and leaders to understand objectives and translate them into clear technical requirements for data, reporting, and advanced analytics.

• Frame technical options as business decisions—articulating cost, risk, time‑to‑value, and long‑term implications so leaders can choose with confidence.

• Influence business stakeholders toward sustainable solutions, including the ability to constructively push back on requests that create long‑term cost, risk, or complexity.

• Ensure data solutions support accuracy, accessibility, governance, and regulatory compliance.

• Act as a design authority during delivery, ensuring solutions meet business intent while remaining technically sound.

Data Integration and Enablement

• Design integration patterns to move and share data across systems using APIs, services, and pipelines.

• Enable downstream consumption by analytics, BI, and AI platforms through well‑structured, well‑documented data products.

• Reduce point‑to‑point integrations by promoting reusable, scalable data patterns and driving their adoption across teams.

Strategic Data Planning

• Shape and influence multi‑year data roadmaps that prioritize high‑value use cases while avoiding data redundancy and unmanaged“data swamps.”

• Partner with platform, governance, and enterprise architecture teams to align solution designs with enterprise standards and capabilities—and to evolve those standards where they no longer serve the business.

• Identify opportunities to simplify, consolidate, or modernize existing data solutions, and build the business case needed to fund and sequence that work.

• Advise leadership on build‑versus‑buy decisions, platform selection, and the architectural implications of strategic investments.

Security, Scalability, and Reliability

• Design secure data environments that follow Protective’s security, privacy, and access‑control policies.

• Ensure solutions scale to support increasing data volumes, complexity, and business demand.

• Incorporate resiliency, monitoring, and operational considerations into solution designs.

Mentorship and Capability Building

• Mentor data engineers and less experienced architects, raising the overall design and technical judgment of the data organization.

• Lead design reviews and architecture working sessions that develop others while improving outcomes.

• Create durable artifacts—reference architectures, design patterns, decision records, and documentation—that scale the architect’s judgment beyond their personal involvement.

• Contribute to hiring, technical assessment, and the development of the broader data community of practice.

Key Capabilities

Technical Depth

• Strong understanding of modern data architectures, including data lakes, data warehouses, and streaming or batch pipelines.

• Proven ability to design solutions that integrate data across multiple systems and domains.

• Ability to translate business problems into practical technical designs without over‑engineering.

• Working knowledge of cloud‑native architectures, data security principles, and scalable design patterns.

• Comfort operating in a delivery‑oriented environment alongside engineers, analysts, and product teams.

Leadership and Influence

• Demonstrated ability to lead and drive outcomes without formal authority, earning credibility through expertise, consistency, and follow‑through.

• Skilled at building consensus among stakeholders with different priorities, incentives, and technical perspectives—and at making a clear call when consensus is not achievable.

• Able to communicate and defend technical positions effectively with audiences ranging from hands‑on engineers to senior business executives.

• Comfortable operating amid ambiguity, competing demands, and incomplete information; brings structure and direction to unclear problem spaces.

• Strong facilitation skills in design reviews, architecture forums, and cross‑functional working sessions.

• Sound judgment about when to enforce a standard, when to allow a pragmatic exception, and when to escalate.

• Genuine interest in developing others and strengthening the technical capability of the wider organization.

Qualifications

Required Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field, or equivalent experience.

• Significant progressive experience in data engineering, data architecture, or solution architecture, including substantial time in a senior technical or architect‑level capacity.

• Demonstrated experience serving as a technical leader or design authority on significant data initiatives spanning multiple teams or business domains.

• Experience designing data solutions that support analytics, reporting, or AI/ML use cases.

• Hands‑on experience with cloud data platforms and modern data technologies.

• Proven track record of influencing technical direction and driving adoption of standards or patterns across teams the individual did not manage.

• Experience partnering directly with business leadership to shape priorities, frame trade‑offs, and support investment decisions.

• Strong communication skills with the ability to explain technical concepts to non‑technical stakeholders and to present recommendations to senior leadership.

• Experience mentoring engineers or other architects.

Preferred Qualifications

• Experience in financial services, insurance, or other regulated industries.

• Familiarity with data governance, security, and compliance requirements, including experience partnering with governance and risk functions.

• Experience supporting AI, machine learning, or advanced analytics solutions.

• Background working in agile or product‑oriented delivery models.

• Experience participating in or presenting to enterprise architecture review boards or similar governance forums.