TradeStation

Enterprise Data Products & Solutions Director

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Employee Type

Full-Time

Location

USA (Remote)

Job Type

Brokerage/Product Strategy

Job ID

3334

#WeAreTradeStation
Remote Position - must reside in Florida, Texas, Illinois, New York, New Jersey, Colorado, Idaho, Massachusetts, Michigan, Minnesota, Missouri, North Carolina, South Carolina, Utah or Virginia

Who We Are:

TradeStation is the home of those born to trade. As an online brokerage firm and trading ecosystem, we are focused on delivering the ultimate trading experience for active traders and institutions. We continuously push the boundaries of what's possible, encourage out-of-the-box thinking, and relentlessly search for like-minded innovators.
At TradeStation, we are building an AI-First culture. We expect team members to embrace AI as a core part of their daily workflow, whether that's using AI to accelerate development, enhance decision-making, improve client outcomes, or streamline internal processes. We hire, grow, and promote people who can harness AI responsibly and creatively. We treat AI as a partner in problem-solving, not just a tool; following our governance standards to ensure AI is used ethically, securely, and transparently. If you join us, you're joining a culture where AI is how we work.
Are you ready to make yourself at home?

What We Are Looking For:

We are looking for an Enterprise Data Products & Solutions Director to drive and lead TradeStation's enterprise data strategy end to end. Reporting directly to the VP of Enterprise Data & AI, this role will be an owner for data products and solutions across the organization — directing the multi-year vision, driving the operating model, and being accountable for the business outcomes of the entire data domain, not a single product or roadmap.
This is an individual-contributor leadership role. The Director will lead through execution, technical authority, and organization-wide influence — driving the strategy, standards, and operating model that Product, Engineering, Data Science, and business teams execute against. This role will be expected to own the area and its results: define priorities, hold teams across the organization accountable to outcomes, and represent the data function to leadership.
A core mandate of this role is to lead TradeStation's transition from project-based, report-centric data delivery to a governed, productized data foundation — treating data as a product with clear owners, quality standards, and measurable adoption and value. This role will take ownership of the organization's hardest data problems — governance at scale, data quality and trust, platform and pipeline modernization, semantic layer design, and AI-enabled data workflows — and drive them to resolution across organizational boundaries.
If you're the type of leader who owns an area outright, sets the direction others follow, and is energized by building an enterprise data capability from the front, this role offers the autonomy, visibility, and impact you're looking for.

What You'll Be Doing:

Own & Lead the Data Product Area
  • Own the enterprise data product vision, strategy, and multi-year roadmap — set the direction and investment priorities for the entire data domain and connect them to TradeStation's business strategy; make the hard prioritization calls on where scarce resources go
  • Be accountable for area-level outcomes — own the OKRs and business results of the data function as a whole, accountable for adoption, quality, trust, and business impact regardless of which team performs the work
  • Lead the organization's transition to "data as a product" — drive the shift from bespoke, project-based data delivery to standardized, governed, reusable data products with clear owners and single sources of truth
  • Define the operating model and standards — establish the prioritization frameworks, delivery standards, and ways of working that let the data area scale and run predictably across teams
  • Serve as the executive- and Board-facing authority on data — partner with the VP of Enterprise Data & AI and senior leadership; represent the data function in leadership, planning, and Board-level reviews and be the accountable owner leadership turns to
Data Products, Platform & Solutions
  • Lead enterprise data product development — set requirements and direction for data products, pipelines, and platforms that meet enterprise needs; write production-grade SQL and Python to validate solutions and establish technical standards by example
  • Own the semantic layer strategy — define the business-friendly metrics, definitions, and data models that ensure a single source of truth across analytics and reporting
  • Set data architecture direction with Engineering — shape the modernization of data models, pipelines, and workflows in Databricks or Snowflake; drive adoption of best practices across teams
  • Drive the value of data products and solutions — define and track the business value of data products; identify opportunities to turn proprietary and market data into high-value internal solutions and, where applicable, externally facing or monetizable data products, partnering with business and go-to-market stakeholders
  • Own third-party and market data sourcing — evaluate, integrate, and manage relationships and licensing for external and market data sources that power TradeStation's data products
Data Governance, Quality & Documentation
  • Establish and own enterprise data governance — design and institutionalize frameworks for data classification, quality standards, lineage tracking, access controls, and metadata management as company-wide policy
  • Drive enterprise data quality and trust — define monitoring, remediation strategies, and quality KPIs; hold teams across the organization accountable to trusted, reliable data
  • Leverage AI for data quality and pipeline optimization — champion and operationalize AI tools (Claude, LLMs) to automate data profiling, anomaly detection, documentation generation, and pipeline troubleshooting at scale
  • Own regulatory and compliance alignment — ensure enterprise data practices meet financial services requirements and internal security/privacy policies; partner with Compliance and Risk and support regulatory examinations and audits
Enablement, Adoption & Organizational Leadership
  • Build enterprise self-service data capabilities — direct the documentation, training, and tooling that enable stakeholders across the company to discover, understand, and use data effectively
  • Influence and align across the organization — build consensus and drive decisions up, down, and across Product, Engineering, Data Science, EA, and business teams with influence rather than authority
  • Build organizational capability — raise the bar for data product practices across the company; mentor and uplevel PMs, analysts, and engineers and establish reusable systems and clarity even without direct reports
  • Drive adoption and measure impact — track product usage, quality improvements, and business outcomes; report progress tied to measurable value and iterate based on feedback
Strategic Impact & Communication
  • Shape enterprise data strategy and thought leadership — guide decisions on data platform trends, architecture, and capability investments; act as internal expert and external voice for TradeStation's data function
  • Communicate effectively across all levels — present technical strategy to executives and the Board and business strategy to engineering; report outcomes to senior leadership
  • Stay ahead of industry trends — maintain deep expertise in modern data platforms, governance tooling, AI-enhanced data workflows, and emerging best practices

The Skills You Bring:

  • Ownership & Area Leadership — proven ability to own an entire data domain or portfolio, set multi-year strategy, and be accountable for area-level business outcomes — not just deliver a single product or roadmap
  • Strategic Data Leadership — track record driving organizational change (e.g., productizing data) and standing up enterprise data capabilities from vision through execution with full autonomy
  • Executive Presence & Influence — proven ability to influence and advise at the executive and Board level and align cross-functional organizations with influence rather than authority
  • Product Management Excellence — expert at building data product roadmaps, defining requirements and success metrics, and delivering iterative value in agile environments
  • Technical Depth — highly proficient in SQL (complex queries, performance optimization, data modeling) and Python (validation, scripting, automation); able to review code, partner credibly with engineering, and set technical standards
  • Data Platform Expertise — deep hands-on experience with Databricks or Snowflake, including modern data architectures (lakehouse, medallion architecture, data mesh concepts) and platform administration
  • Semantic Layer & Metrics Design — experience designing and implementing semantic layers (e.g., dbt metrics, Cube, AtScale, LookML) and translating business concepts into consistent, reusable definitions
  • Enterprise Data Governance Leadership — proven track record institutionalizing governance frameworks, quality monitoring, metadata management, documentation practices, and compliance controls across complex organizations
  • AI-Enhanced Data Workflows — hands-on experience leveraging AI tools (Claude, LLMs, N8N) to improve data quality monitoring, automate documentation, generate profiling insights, and optimize pipeline development
  • Data Product & Solutions Thinking — strong understanding of how data products enable downstream use cases (BI, ML, operations), a "data as a product" mindset, and familiarity with data monetization/value models
  • Financial Services Domain (strongly preferred) — experience with trading data, market data, regulatory reporting, or financial services compliance requirements
  • Demonstrated experience owning and leading a data domain end to end — setting strategy, driving cross-functional and executive alignment, and delivering organizational change at scale
  • Experience leading the productization of data or building an enterprise data function in a large, matrixed, or regulated environment preferred
  • Advanced proficiency in SQL and hands-on experience with modern data platforms (Databricks, Snowflake, or equivalent) preferred
  • Proven track record implementing enterprise data governance and quality frameworks in production environments preferred
  • Experience designing semantic layers, metrics frameworks, or business-friendly data models at enterprise scale preferred
  • Experience defining data product value/monetization models or managing third-party and market data sourcing and licensing preferred
  • Strong Python skills for data engineering, scripting, and automation preferred
  • Experience leveraging AI/LLMs for data quality, documentation automation, or pipeline optimization preferred
  • Experience with data governance tools (data catalogs, lineage tracking, quality monitoring platforms) preferred
  • Familiarity with data visualization and BI tools (Tableau, Power BI, Looker, Sigma) preferred

Minimum Qualifications:

  • Bachelor's degree in business, finance, computer science, data science, or related technical field
  • 10+ years in data product, platform, or data strategy roles, including demonstrated ownership of an enterprise data area or portfolio with accountability for measurable business outcomes

Desired Qualifications:

  • Advanced degree (MBA or technical master's in CS, data science, or engineering)

Benefits at TradeStation

  • ○Collaborative work environment
  • ○Competitive Salaries
  • ○Yearly bonus
  • ○Comprehensive benefits for you and your family starting Day 1
  • ○Unlimited Paid Time Off
  • ○Flexible working environment
  • ○TradeStation Account employee benefits, as well as full access to trading education materials
  • ○Pay Range (US) $197-225K (Countries outside of the US have differing ranges in accordance with local labor markets)
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TradeStation provides equal employment opportunities to current and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, sexual orientation, age, pregnancy, disability, handicap, citizenship, veteran or marital status, or any other legally recognized status entitled to protection under federal, state, or local anti-discrimination laws.