Data Solutions Architect

Protective • Birmingham, NE

1d • $124,500 - $170,000

About The Position

The Data Solutions Architect is a senior individual contributor who serves as a bridge between business strategy and technical execution, designing end-to-end data solutions that enable analytics, reporting, and AI use cases across the enterprise. This role combines deep data architecture expertise with solution design and technical leadership responsibilities—creating practical, scalable, and secure data solutions that translate business needs into actionable technical roadmaps. This position is embedded closer to delivery teams, working hands-on with business partners, engineers, and product teams to ensure data solutions are usable, compliant, and aligned to Protective’s priorities. While this role has no direct reports, it carries significant leadership accountability. The Data Solutions Architect is expected to set technical direction, drive alignment across independent teams, and influence outcomes through expertise, credibility, and relationships rather than positional authority. Decisions made in this role shape multi-year data investments, establish patterns adopted by multiple engineering teams, and directly affect Protective’s ability to deliver trusted data and AI capabilities at scale.

Requirements

• 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.

Nice To Haves

• 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.

Responsibilities

• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.

Benefits

• Comprehensive health, dental and vision insurance
• Mental health benefits
• Employee assistance program
• Variety of paid time away benefits (e.g., paid time off, paid parental leave, short-term disability, and a cultural observance day)
• Contributions to healthcare accounts
• Pension plan
• 401(k) plan with Company matching
• ProHealth Rewards

What This Job Offers

• Job Type: Full-time
• Career Level: Senior