Technical Product Manager, Data Platforms

Bellwether•Dallas, TX

3d•Hybrid

About The Position

The Technical Product Manager role owns quality assurance and data validation across all Sigma BI and Databricks client implementations. This is your opportunity to be the technical backbone of our platform rollout—ensuring every client migration is data-accurate, every integration is validated, and every deployment is launch-ready. You will work closely with clients and development teams to identify data gaps early, validate migrations rigorously, and build confidence in our analytics infrastructure. The ideal candidate is a technical problem-solver with hands-on expertise in data validation, SQL, and Excel. You thrive in ambiguous, detail-oriented work where small discrepancies matter and precision is mission-critical. You communicate clearly with both technical teams and non-technical clients, and you have a proactive mindset about identifying and escalating risks early.

Requirements

5+ years of market experience and professional working experience
3+ years of product management in business or financial analytics
3+ years of experience in data platform environments
Proven track record managing client implementations or platform rollouts, translating technical requirements into operational plans
Background in product management or cross-functional technical leadership
Strong SQL skills—you can write queries independently to validate data, reconcile tables, and identify discrepancies.
Advanced Excel proficiency—building data validation models, pivot tables, lookups, and audit trails.
Hands-on experience with analytics platforms (Sigma, Tableau, Looker) or data warehouses (Databricks, Snowflake, BigQuery).
Understanding of data migration methodologies, ETL workflows, and schema mapping.
Comfortable diving into data lineage, calculated fields, and dashboard logic to identify accuracy issues.
Strong attention to detail and ability to troubleshoot technical problems methodically.
Excellent ability to explain technical data concepts to non-technical clients.
Proactive in surfacing risks early and escalating smartly.
Strong listening and interpersonal skills—you ask good questions and take time to understand client context.
Comfortable presenting validation results, testing outcomes, and implementation status to mixed-technical audiences.
Ability to perform responsibilities independently and proactively.
Self-directed ownership mindset—you take accountability for quality outcomes and deliver end-to-end.
Strong project management skills and meticulous attention to detail.
Comfort with ambiguous technical problems and autonomous problem-solving.
Acts with honesty and integrity.
Maintains confidentiality and adheres to company policies.
Promotes collaborative, productive working relationships across technical and non-technical teams.
Demonstrates respect and support for cross-functional partners.
Ability to prove eligibility to work in the United States.

Nice To Haves

Strong experience with financial services, commercial real estate, or related preferred.
Experience with real estate, financial services, or asset management workflows
Hands-on experience with Sigma BI, Databricks, or similar modern data platforms
Familiarity with Salesforce and data migrations from legacy systems
Experience building data validation frameworks or audit processes
Background owning client success and managing technical implementations

Responsibilities

Own QA strategy and data validation plan for every Sigma/Databricks client implementation designing tie-out workflows, reconciliation checkpoints, and data quality gates
Write SQL queries and build Excel-based data validation models to reconcile legacy system data identifying gaps and discrepancies before client launch
Validate Sigma dashboards, data sources, and calculated fields against reconciled data ensuring clients see accurate numbers from day one
Build and maintain data quality dashboards and detailed audit reports documenting validation results for client sign-off
Conduct technical discovery calls with clients; document data requirements, system landscape, and identify integration risks upfront
Identify and escalate technical blockers, data quality issues, and integration risks to the Senior PM and development team
Coordinate with data engineering, Salesforce, and infrastructure teams on validation, integration, and deployment issues
Build reusable validation templates, field mapping guides, and implementation checklists that scale across clients