Lead Solutions Architect Jobs

Role Summary:

The Data & Analytics Solutions Architect provides senior, hands-on technical leadership for CRICO's analytics and data initiatives, from solution design through implementation and production readiness. The role owns the end-to-end technical approach across data ingestion, transformation, modeling, semantic layers, BI/reporting, APIs, and integrations—not simply high-level architectural recommendations.

Working across Data Engineering and BI Engineering, this individual establishes clear technical direction, resolves difficult implementation issues, and translates business requirements into executable, supportable solutions. The role also contributes to establishing and operationalizing a unified Technology Delivery Framework, integrating analytics-specific ADLC practices with common enterprise engineering, security, quality, and delivery controls.

The immediate priority is to help strengthen the delivery practices of a critical analytics initiative by identifying architecture, data-modeling, integration, and quality gaps; unblocking engineering teams; and strengthening delivery readiness. Day-to-day technical leadership is core to the position. Formal people-management responsibility is not assumed at hire and may evolve based on organizational needs and demonstrated capability.

Responsibilities:

Solution Architecture & Design

• Translate business and analytics requirements into implementable end-to-end designs spanning data sources, pipelines, storage, logical/physical and dimensional models, semantic layers, reporting, APIs, and integrations.
• Own detailed data architecture and modeling decisions, including data-domain concepts, structures, relationships, grain, metric definitions, and source-to-report traceability.
• Evaluate and document design tradeoffs involving data quality, performance, scalability, cost, privacy, security, supportability, and long-term maintenance.
• Define reusable solution patterns and technical approaches aligned with CRICO technology strategy and architecture guardrails.

Technical Leadership & Delivery

• Provide day-to-day technical leadership across Data Engineering and BI Engineering, with clear ownership, timely decisions, and coordinated upstream and downstream work.
• Turn architecture into actionable implementation plans, including technical dependencies, sequencing, estimates, risks, and readiness criteria; partner with project leadership on delivery commitments.
• Resolve complex technical issues directly through prototyping, coding or pairing, troubleshooting, technical reviews, and hands-on problem-solving.
• Establish and reinforce acceptance criteria, a consistent definition of done, engineering and quality gates, proactive defect management, and production-readiness reviews.
• Identify skill, capacity, and technical risks early; communicate impacts and escalate material blockers with practical mitigation options.
• Mentor engineers and delegate implementation decisions within agreed standards, reinforcing accountability without unnecessary process or centralized bottlenecks.

Data & Analytics Engineering

• Guide implementation of robust data pipelines, transformations, data models, semantic layers, reporting solutions, and integrations from source systems through consumption.
• Help establish and operationalize consistent ADLC practices across Data Engineering and BI Engineering, including source profiling, data quality, lineage, reconciliation, metric and semantic validation, business validation, and ongoing data-product monitoring.
• Improve automated testing, deployment, CI/CD, observability, documentation, and production support across analytics solutions.
• Identify and address technical debt, inconsistent modeling practices, reliability gaps, and opportunities for reuse and engineering efficiency.

Architecture & Standards

• Serve as the technical architecture owner for analytics solutions, leading detailed data design while coordinating cross-domain decisions with Application Engineering, DBA, Security, and other partners.
• Partner with Technology Engineering leadership to define, refine, and operationalize the shared Technology Delivery Framework, integrating analytics-specific ADLC practices with common architecture, security, quality, testing, change management, release, and operational-readiness controls.
• Document key architecture decisions, dependencies, and tradeoffs; balance longer-term standards with pragmatic, iterative delivery.

Collaboration & Mentoring

• Collaborate with business stakeholders, product owners, BSAs, project/program managers, DBAs, application engineers, cloud/infrastructure teams, Security, and the independent QA organization.
• Communicate complex technical decisions and business-data concepts clearly, maintaining alignment between requirements, implementation, validation, and operational expectations.
• Build technical capability and a unified engineering culture through mentoring, design reviews, knowledge transfer, and shared standards of ownership, quality, rigor, and predictability.

Qualifications:

Education & Experience:

• Bachelor's degree in computer science, engineering, information systems, or a related field preferred; equivalent practical experience considered.
• Typically 10+ years of relevant engineering or architecture experience, including substantial hands-on delivery of complex production data and analytics solutions; equivalent demonstrated depth is valued over tenure alone.
• Proven track record owning the technical design and hands-on delivery of enterprise-scale data and analytics solutions spanning data engineering and BI/reporting.
• Demonstrated technical leadership across teams, including architecture decisions, complex troubleshooting, mentoring, and resolution of delivery-critical issues.
• Practical experience with data quality, reconciliation, test automation, code/design review, release readiness, and operational monitoring.
• Experience with relevant technologies such as AWS/Azure, Snowflake, SQL Server, Power BI, and modern data integration/ELT platforms (including Fivetran or equivalents) preferred.
• Experience in healthcare, insurance, or other regulated environments involving sensitive data preferred.
• Experience improving analytics delivery practices (ADLC), engineering standards, CI/CD, and iterative delivery across multiple teams preferred.
• People-leadership experience or demonstrated potential to assume formal management responsibilities as the organization evolves preferred

• Deep proficiency in SQL, data integration, ETL/ELT, data warehousing/cloud data platforms, and logical, physical, dimensional, and semantic data modeling.
• Ability to understand and explain intricate business data domains, establish reliable definitions, and translate them into tested, traceable data products.
• Sound judgment regarding security, privacy, data governance, performance, scalability, maintainability, and architectural tradeoffs.
• Strong communication, cross-functional coordination, prioritization, and early risk-identification skills.
• Exposure to AI-enabled analytics or agentic solutions is a plus

Specialized Certifications: N/A

People Management: No direct people management responsibilities

The expected salary range for this position is $150,000 to $170,000 annually. This represents the employer’s good faith estimate of the compensation range at the time of posting. Final compensation will be based on factors such as experience, education, and qualifications.