Senior Solutions and Data Architect - Asset Management

ThriventMinneapolis, MN
$161,072 - $217,920Hybrid

About The Position

The Senior Solutions and Data Architect is a trusted advisor responsible for setting architectural direction and advancing technical excellence across Asset Management. This role is a subject matter expert who leads both data and solution architecture for critical investment vendor platforms and internally built applications, ensuring scalable, secure, and well-governed systems that support research, portfolio management, trading, operations, and downstream reporting workflows. This role partners closely with the business, analysts and engineering teams to translate business needs into technical designs and a clear, phased roadmap balancing rapid delivery with long-term architectural integrity. Additionally, in collaboration with Thrivent’s corporate IT function, this architect establishes architecture patterns and data product standards (metadata, lineage, quality, access controls, and regulatory traceability), advises on master data management and entity resolution for critical investment domains, and helps enable front-to-back workflow connectivity across investment, operations, and reporting processes. This role is also responsible for evaluating and guiding adoption of modern data platforms through proofs of concept and benchmarks, shaping architecture decisions across internal and vendor platforms, and helping modernize both cloud and legacy environments with resilient, secure integration patterns. The Senior Solutions and Data Architect identifies and validates high-value AI and emerging-technology use cases, defines reusable guardrails in partnership with security/risk/compliance/enterprise architecture. Finally, the architect is expected to provide hands-on leadership through mentoring, coaching, and enabling a culture of continuous improvement.

Requirements

  • Bachelor’s degree in Computer Science, Information Systems, Engineering, or equivalent experience.
  • Minimum of 8 years in architecture and/or senior engineering roles, with deep experience in data architecture for complex domains.
  • Financial Services experience with Asset Management / Capital Markets domain knowledge, including familiarity with investment research, portfolio, trading, operations, risk, and reporting workflows.
  • Experience in complex engineering environments, taking abstract concepts and ideas and formulating a detailed software engineering plan to deliver.
  • Strong background in data modeling (conceptual/logical/physical), integration patterns, metadata/lineage, and data governance operating models, ideally in support of investment workflows.
  • Experience designing modern data platforms (Snowflake, Databricks, lake house, dbt) and working effectively with data engineering and application engineering teams using cloud-native deployment practices.
  • Hands-on understanding of distributed data processing, orchestration, and observability concepts (batch and streaming where applicable), including the ability to prototype and troubleshoot pipelines and integrations.
  • Ability to communicate architecture clearly to both business and technology audiences; comfortable influencing in ambiguous, multi-stakeholder environments.
  • Proven leadership experience to train and partner with peers, stakeholders and teams.
  • Demonstrated successful problem-solving skills with ability to work through ambiguity.

Nice To Haves

  • Experience with investment platforms, front-office technology, and data ecosystems (e.g., Aladdin Studio, FactSet API and MCP offering, Bloomberg DL+) and associated integration patterns.
  • Familiarity with data cataloging/governance platforms and practices (business glossary, stewardship workflows, automated lineage).
  • Exposure to AI/agentic architectures, including safe tool use patterns and standardization approaches such as MCP servers.
  • Production AI experience strongly preferred.
  • Programming/scripting experience (e.g., Python, SQL; Java a plus) with comfort producing prototypes/reference implementations and participating in code reviews.

Responsibilities

  • Shape the modern data architecture, translating front-office investment and operations needs into a clear, phased roadmap.
  • Own core investment data models and standards (IBOR, ABOR, PBOR, and other related data sets) with consistent, canonical definitions.
  • Define patterns for processing unstructured and semi structured data sets.
  • Establish data product standards aligned with enterprise architecture to ensure data is reliable, governed, compliant, and fit for analytics, risk, reporting, operational, and front-office investment workflows.
  • Contribute hands‑on expertise to data governance, including metadata, lineage, data quality, and regulatory traceability.
  • Evaluate and guide adoption of modern data platforms (e.g., Snowflake, Databricks), using proof of concepts and benchmarks to inform design decisions.
  • Partner closely with investment data enablement team to design solutions, review implementations, and facilitate delivery.
  • Develop data security, access controls, and privacy requirements.
  • Establish data observability and reliability practices to monitor pipeline health, quality, and SLAs.
  • Partner with investment and technology teams to translate business needs into scalable solution designs and roadmaps that support front office, operational, and reporting workflows.
  • Design end‑to‑end architectures and integration patterns across internal and vendor platforms, ensuring reliable data flow, security, and resilience.
  • Work hands‑on with engineering teams throughout delivery to refine designs, validate patterns, remove architectural blockers, and ensure solutions work as intended in production.
  • Define and promote architecture patterns and engineering standards in partnership with corporate IT and enterprise architecture, ensuring consistent adoption across teams.
  • Provide architectural leadership for large programs, platform modernization, and vendor/platform evaluations, influencing buy, build, and integration decisions.
  • Review and approve solution designs to ensure alignment with enterprise standards, security, and operating needs.
  • Lead cloud and legacy modernization efforts, including guidance on multi‑region, resilient architectures.
  • Contribute code and automation as needed (e.g., services, infrastructure templates, accelerators).
  • Support agile delivery by balancing rapid iteration with long‑term architectural integrity.
  • Validate high‑value AI use cases across Asset Management using proofs of concept to demonstrate value, feasibility, and governance.
  • Define secure, reusable AI architectures and guardrails (e.g., agent patterns, MCP-style integration, access controls, auditability) in partnership with enterprise architecture, security, risk, and engineering teams.
  • Continuously assess emerging technologies, including engineering productivity tools, to drive efficiency, accuracy, and faster delivery.
  • Provide leadership by mentoring, coaching, and developing analysts and engineers through a hands-on, team-based partnership approach.
  • Model Thrivent’s leadership competencies — courage, collaboration, and commitment — by demonstrating resiliency, making thoughtful decisions, and holding self and others accountable.
  • Support and foster an environment focused on continuous improvement, exceptional employee engagement, and unwavering commitment to clients.
  • Shapes a culture aligned to Thrivent’s purpose, promise, and values, ensuring trust and reputation remain strong.
  • Model Thrivent’s leadership competencies – Model the Way, Rally the Team, and Deliver Outcomes.
  • Embrace and support an environment in which Thrivent employees and colleagues are focused on continuous improvement, exceptional employee engagement, and an unwavering commitment to our clients.
  • Support a culture that represents the Thrivent purpose, promise and values, ensuring that Thrivent’s trust and reputation remain strong with its clients.

Benefits

  • various bonuses (including, for example, annual or long-term incentives)
  • medical, dental, and vision insurance
  • health savings account
  • flexible spending account
  • 401k
  • pension
  • life and accidental death and dismemberment insurance
  • disability insurance
  • supplemental protection insurance
  • 20 days of Paid Time Off each year
  • Sick and Safe Time
  • 10 paid company holidays
  • Volunteer Time Off
  • paid parental leave
  • EAP
  • well-being benefits
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