Who You'll Work With:

The Investment Technology team is seeking a Nashville, TN based Technical Writer to own and evolve documentation for our investment data and analytics platforms. You will play a critical role in making complex data systems understandable, discoverable, and usable for investment professionals and technologists alike. This role is ideal for someone who excels at technical communication, enjoys working at the intersection of data and investments, and is passionate about enabling clarity, governance, and AI‑ready knowledge at scale.

You will work closely with data engineers, architects, product owners, and investment stakeholders to ensure that technical concepts are clearly documented, consistently described, and optimized for both human and AI‑assisted consumption.

What You’ll Do:

You will serve as the technical writer and documentation lead for investment data platforms and analytics solutions. The role focuses on authoring, structuring, and maintaining technical documentation that explains how investment data is sourced, modeled, governed, accessed, and used across research, portfolio management, risk, and analytics workflows.

• Author and maintain clear, accurate documentation for data pipelines, datasets, semantic models, APIs, and analytics products.

• Produce architecture overviews, data flow diagrams, data dictionaries, and usage guides for investment data assets.

• Translate complex engineering and investment concepts into consumable documentation for technical and non‑technical audiences.

• Document data models, schemas, business definitions, and relationships across fixed income, equities, and multi‑asset domains.

• Maintain standardized templates for data definitions, metrics, and calculated fields to ensure consistency across platforms.

• Partner with engineering teams to keep documentation aligned with evolving data structures and releases.

• Build working knowledge of key investment data domains (reference data, pricing, terms & conditions, indices, risk inputs).
  

• Clearly document how data inputs flow into analytics, models, and reporting outputs used by investment teams.

• Ensure documentation reflects both technical design and business usage context.

• Structure documentation so it can be effectively consumed by AI assistants (e.g., Copilot, internal LLMs).

• Apply consistent metadata, tagging, and taxonomy standards to improve discoverability and retrieval.

• Design documentation hierarchies and knowledge bases that support natural‑language search and AI‑driven Q&A.

• Contribute to data governance documentation, including standards, best practices, and usage guidelines.

• Partner with data governance, architecture, and security teams to document controls, access patterns, and compliance considerations.

• Support adoption of enterprise catalogs (e.g., Purview) through high‑quality descriptive content.

• Work closely with data engineers, architects, product managers, and investment teams to gather content and validate accuracy.

• Facilitate documentation reviews and ensure alignment across technology and business stakeholders.

• Act as a steward of documentation quality, clarity, and consistency across the investment data ecosystem.

What We’re Looking For:

• Proven experience authoring technical documentation for data platforms, analytics systems, or enterprise technology.

• Strong ability to translate complex technical concepts into clear, structured written content.

• Experience creating architecture diagrams, data flow documentation, and structured knowledge bases.

• Working understanding of data concepts such as data pipelines, ETL/ELT, data modeling, semantic layers, and BI tools.

• Familiarity with data platforms such as Databricks, Snowflake, Synapse, or similar (documentation focus, not hands‑on build).

• Exposure to analytics tools like Power BI or Excel from a documentation and enablement perspective.

• Understanding of how documentation supports AI tools, search, and retrieval‑augmented generation (RAG).

• Experience structuring content for discoverability, reuse, and automated interpretation.

• Documentation tools such as Confluence, SharePoint, Markdown‑based systems, or similar knowledge platforms.

• Experience working with metadata catalogs (e.g., Microsoft Purview or equivalents) is a plus.

• Exceptional written communication and attention to detail.

• Ability to work cross‑functionally with engineers, architects, and investment professionals.

• Strong organizational skills and comfort managing documentation across multiple initiatives.