Note: The job is a remote job and is open to candidates in USA. TradeStation is an online brokerage firm focused on delivering an exceptional trading experience for active traders and institutions. They are seeking an Enterprise Data Senior Product Manager to lead the execution of their data strategy, ensuring a world-class enterprise data foundation that powers analytics and AI across the organization.
Responsibilities
- Own the data platform roadmap — independently assess current state, identify gaps, and drive initiatives that establish a solid data foundation for analytics, AI, and business operations
- Manage the data product development — define requirements and deliver data products, pipelines, and platforms that meet enterprise needs; write production-grade SQL and Python to validate solutions and set technical direction
- Help build and maintain the semantic layer — design business-friendly metrics, definitions, and data models that ensure consistency across analytics and reporting; hands-on configuration and documentation of semantic layer tools
- Partner with data engineering to modernize data architecture — design and optimize data models, pipelines, and workflows in Databricks or Snowflake; drive adoption of best practices
- Establish enterprise data governance — design and implement frameworks for data classification, quality standards, lineage tracking, access controls, and metadata management
- Ensure comprehensive data documentation — create and maintain clear documentation of data assets, business definitions, lineage, and usage patterns; make data discoverable and understandable for all stakeholders
- Leverage AI for data quality and pipeline optimization — use AI tools (Claude, LLMs) to automate data profiling, anomaly detection, documentation generation, and pipeline troubleshooting
- Drive data quality initiatives — proactively identify data quality issues, define monitoring and remediation strategies, and hold teams accountable to quality KPIs
- Ensure regulatory compliance — align data practices with financial services requirements and internal security/privacy policies
- Build self-service data capabilities — create documentation, training, and tooling that enable stakeholders across the company to discover, understand, and use data effectively
- Act as data platform advocate — work with Product teams, Analytics, and business stakeholders to understand needs and translate them into scalable platform solutions
- Drive adoption and measure impact — track platform usage, quality improvements, and business outcomes; iterate based on feedback
- Shape data strategy — contribute thought leadership on data platform trends, architectural decisions, and capability investments
- Communicate effectively across levels — present technical concepts to business audiences and business requirements to engineering teams; report progress tied to measurable outcomes
- Stay ahead of industry trends — maintain expertise in modern data platforms, governance tools, AI-enhanced data workflows, and emerging best practices
Skills
- Bachelor's degree in business, finance, computer science, data science, or related technical field
- 7+ years in data product or platform roles, including demonstrated ownership of enterprise data initiatives with measurable business impact
- Self-Starter & Strategic Thinker — proven ability to independently assess complex data landscapes, identify high-impact opportunities, and drive initiatives from strategy through execution without heavy oversight
- Product Management Excellence — expert at building data product roadmaps, writing clear requirements and acceptance criteria, defining success metrics, and delivering iterative value in agile environments
- Technical Depth — highly proficient in SQL (complex queries, performance optimization, data modeling) and Python (data validation, scripting, automation); able to review code 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); ability to translate business concepts into consistent, reusable data definitions
- AI-Enhanced Data Workflows — hands-on experience leveraging AI tools (Claude, LLMs) to improve data quality monitoring, automate documentation, generate data profiling insights, or optimize pipeline development
- Data Governance Leadership — proven track record implementing enterprise data governance frameworks, quality monitoring, metadata management, comprehensive documentation practices, and compliance controls in complex organizations
- Cross-Functional Leadership — skilled at influencing without authority; ability to build consensus across Product, Engineering, Analytics, and business teams; comfortable presenting to executives
- Analytics & Data Product Thinking — strong understanding of how data products enable downstream use cases (BI, ML, operations); familiarity with analytics workflows and tooling
- Financial Services Domain (strongly preferred) — experience with trading data, market data, regulatory reporting, or financial services compliance requirements
- Advanced proficiency in SQL and hands-on experience with modern data platforms (Databricks, Snowflake, or equivalent) preferred
- Proven track record of implementing data governance and quality frameworks in production environments preferred
- Experience designing semantic layers, metrics frameworks, or business-friendly data models 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
- Advanced degree in a relevant field (e.g., Computer Science, Financial Engineering, Data Science, MBA)
Benefits
- 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
Company Overview
Company H1B Sponsorship