The Role
Own and maintain the data catalog, vendor and licensing records, dataset lineage, field definitions, and calculation documentation. Write SQL to trace, join, reconcile, and validate data; investigate discrepancies; QA derived metrics; prepare data extracts; and troubleshoot issues with engineering, offshore data teams, PMO, and customer service. Use AI tools to accelerate data work and maintain clear documentation for technical and non-technical stakeholders.
Summary Generated by Built In
About TradeSmith
TradeSmith builds investment research tools and data infrastructure for individual investors and financial publishers. Our platforms power TradeSmith's own product suite and the data tools behind InvestorPlace, one of the largest independent financial publishers in the US. The vendors, datasets, and calculations underneath all of it -- that's what this role owns.
The Role
We need someone who actually wants to live in the data. Not manage it from a distance, not hand it off -- own it.
This is a hands-on individual contributor role on our data, algorithm, and calculations team. You are the person who can answer "where does this number come from, what are we allowed to do with it, and is it right?" -- and then go prove it.
The center of gravity is our data catalog: the vendors we buy from, the datasets they provide, the thousands of fields we store, and the calculations we build on top of them, spanning both TradeSmith's product suite and InvestorPlace's tools.
Strategy and delivery oversight sit with the Director of Technology Operations. Your job is execution inside the data -- tracing lineage, writing SQL, validating calculations, troubleshooting issues, and documenting what you find. You will work alongside our existing team and partner daily with our offshore development and data team.
This is also a growth seat. The right person is someone we can develop into broader data leadership as the team and platform mature. That requires genuine curiosity about the business, not just the data.
What You'll Be Doing
Data Catalog and Lineage (primary focus)
- Own and maintain our data catalog -- vendors, datasets, fields, and calculations -- keeping every entry current as the underlying data and agreements change
- Trace individual fields and calculated values back to their original source; the lineage of any number should be documented and defensible
- Keep confidence and status markers honest (confirmed vs. draft) and work the open-items queue down rather than letting unknowns accumulate
- Document data usage and licensing constraints per vendor -- what we can and cannot show customers
Hands-On Data Work and QA
- Write your own SQL to pull, join, trace, and validate data -- no waiting on someone else to run queries for you
- Validate calculation engines and derived metrics against their inputs; reconcile figures across datasets and products
- Investigate discrepancies end to end and flag root causes clearly
- Prepare clean, well-labeled data inputs and extracts for the engineering and offshore teams
Support and Troubleshooting
- Partner with the PMO on intake: help triage and validate data-related requests entering the queue
- Support the broader data, algorithm, and calculations team with hands-on troubleshooting
- Help Customer Service investigate reported data issues -- "why hasn't the closing price updated?" -- and provide clear answers or route them to the right owner
Vendor Coordination
- Track what each vendor agreement licenses us to receive and use; surface renewals, gaps, and usage-rights questions to the Director of Technology Operations
- Keep the data holdings record accurate enough that leadership can rely on it for decisions and audits
AI-Assisted Tooling
- Use AI tools (Claude and similar) to accelerate data mapping, documentation, and repetitive data tasks
- Help shape how those tools fit into our workflows and contribute hands-on to the next iteration of our data platform
Documentation
- Keep documentation current and readable -- "ask the Data Analyst" and "check the catalog" should give the same answer
- Write findings and summaries plainly for both technical and non-technical readers
What We're Looking For
- 2+ years in a hands-on data role -- data analyst, data coordinator, data steward, reporting analyst, or similar
- Working SQL proficiency: you write your own queries to trace, join, and validate data
- Strong spreadsheet skills (Excel or Google Sheets), including comfort with large and messy datasets
- Exceptional attention to detail and follow-through; you get real satisfaction from accuracy and getting the small things right
- Clear written communication; your documentation can stand on its own
- Self-directed -- you thrive on execution in an environment where processes exist but are still being built
- Interest in growing into broader data responsibility over time
Nice to have:
- Fintech, financial services, or media/publishing data background
- Familiarity with data catalogs, data lineage, or data governance concepts
- Experience using AI tools (Claude, Copilot, ChatGPT) to accelerate data work
- Exposure to BI tools (Tableau, Power BI, Looker) or Snowflake
- Understanding of financial calculations and market data
- Russian language skills -- our offshore data team speaks Russian; helpful, not required
Location: Baltimore, MD -- Hybrid (Remote considered for highly qualified candidates)
Salary Range: $85,000 - $110,000
Equal Opportunity
As an employer committed to equal opportunity and a diverse workforce, all qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
The base pay range for this role is $85,000 – $110,000 per year.
Skills Required
- 2+ years of experience in a hands-on data role such as data analyst, data coordinator, data steward, or reporting analyst
- Working proficiency in SQL, including writing queries to trace, join, and validate data
- Strong spreadsheet skills using Excel or Google Sheets, including handling large and messy datasets
- Exceptional attention to detail and follow-through
- Clear written communication and ability to produce standalone documentation
- Self-directed execution in an environment where processes are still being built
- Interest in growing into broader data responsibility
- Background in fintech, financial services, or media/publishing data
- Familiarity with data catalogs, data lineage, or data governance concepts
- Experience using AI tools such as Claude, Copilot, or ChatGPT
- Exposure to BI tools such as Tableau, Power BI, or Looker, or to Snowflake
- Understanding of financial calculations and market data
- Russian language skills
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The Company
What We Do
Midwestern Interactive, LLC is a U.S.-based software and product development firm that delivers cloud and mobile applications, digital strategy, and creative/media services. The company provides scoped projects, embedded engineering teams, and recruiting/talent services to help clients accelerate product development and scale technical capability. Founded in 2012 and headquartered in Joplin, MO, Midwestern focuses on end-to-end product delivery and talent partnerships for growing businesses.
