VP, Data Products & Platform Lead

About the Role

The firm is seeking a founding lead for data products and platform to define, govern, and ship core investment data while growing a small team around this critical function. You will operate at the center of a federated model where portfolio management, trading, portfolio administration, finance, research, and compliance currently build with the firm's data, and you will convert this fragmented energy into trusted, shared, and governed products. This is a player-coach position that requires hands-on coding alongside setting product direction, writing production SQL and Python, and hiring as the function scales. You will own the lifecycle of data offerings, turning recurring needs into versioned, discoverable, and well-documented canonical assets that the entire firm reuses.

Key facts

What you'll do

Establish the firm's first intake, prioritization, and roadmap for data work, replacing ad-hoc triage with a visible, defensible backlog that aligns with business outcomes.

Reconcile divergent definitions used by each function into a single set of canonical, documented entities, including fund and security master, holdings, classifications, corporate actions, index data, and associated identifiers.

Own the data-product lifecycle by turning recurring requirements into governed shared products with clear ownership, service-level agreements, and a discoverable catalog that makes the canonical layer the default choice.

Drive adoption of shared data products by increasing the number of teams that rely on the governed layer instead of querying raw vendor tables directly.

Write production dbt models in Python and SQL and design serving and semantic layers, ensuring that implementation details align with product requirements and compliance constraints.

Harden platform reliability through alerting on data freshness and pipeline runs, workload isolation, least-privilege service accounts, and monitored, managed ingestion processes.

Partner with technology and business teams on market data and internal reporting consolidation, including Bloomberg and FactSet integrations, to make the canonical layer the obvious and safe starting point for AI-assisted building across the firm.

Build and lead a small, senior data team while mentoring embedded analysts and existing engineers to elevate data practices across the business.

Establish the operating model for data products, including shared repositories, review and approval workflows, and standards, acting as reviewer and enabler rather than gatekeeper.

Serve as the firm's senior voice on data matters, translating complex technical and regulatory topics into clear decisions for executives, business stakeholders, and compliance leadership.

Requirements

Bring 8+ years of experience in data roles, with a genuine blend of hands-on data engineering and data-product ownership, including shipped pipelines, models, definitions, and roadmaps.

Demonstrate deep buy-side or asset-management data domain knowledge, covering security and fund master, holdings, transactions, corporate actions, benchmarks and index constituents, identifiers, and NAV, as well as vendor feeds from Bloomberg, FactSet, and fund-accountant data sources.

Write expert SQL and Python and possess production experience with Snowflake and dbt or close equivalents, ensuring robust, performant, and maintainable implementations.

Show demonstrated ownership of a canonical data model or data standards that have been adopted across multiple consuming teams, with evidence of governance and clarity.

Have a track record of building and leading a small data team or show clear, evidenced readiness to step into a founding-lead role with strong influence.

Communicate clearly in writing and verbally, with the ability to set definitions and defend prioritization decisions to executives, business stakeholders, and compliance functions.

Understand ETF and 1940-Act fund structures, including SEC recordkeeping under Rule 204-2, Regulation S-P, 15(c) board reporting, and the Tailored Shareholder Reports regime.

Leverage modern data stack components such as data catalogs including OpenMetadata or Atlan, orchestration tools like Airflow or MWAA, managed ingestion, business intelligence with Sigma, Snowflake Cortex, and semantic views.

Hands-on experience with AI-assisted engineering tools such as Claude Code, Codex, or Kiro, and experience building self-serve, semantic, or agent layers over governed data.

Operate comfortably in an AWS environment and use Terraform or infrastructure-as-code practices, with experience establishing data governance in regulated environments.

Nice to have

Only if the candidate has ETF / 1940-Act fund experience, familiarity with SEC recordkeeping (Rule 204-2), Regulation S-P, 15(c) board reporting, and the Tailored Shareholder Reports regime.

Only if the candidate has used modern data stack components such as data catalogs including OpenMetadata or Atlan, orchestration tools like Airflow or MWAA, managed ingestion, business intelligence with Sigma, Snowflake Cortex, and semantic views.

Only if the candidate has hands-on experience with AI-assisted engineering tools such as Claude Code, Codex, or Kiro, and experience building self-serve, semantic, or agent layers over governed data.

Only if the candidate has AWS and Terraform or infrastructure-as-code experience, with a track record of standing up data governance in regulated environments.

Practical notes

Global X does not accept unsolicited resumes or candidate profiles from recruitment agencies, search firms, or third-party recruiters.

Compensation range for this role is $220,000 to $230,000 plus annual bonus.

The role is full-time, based in New York, NY, and operates in a hybrid work environment.

The firm offers comprehensive benefits, including competitive base salary with annual performance-based bonus, medical, dental, and vision insurance, 401(k) with company matching, generous paid time off and company holidays, professional development opportunities, life and disability insurance, wellness programs, and employee assistance programs.

Global X was founded in 2008. For more information about the company, visit the about page on the Global X website.