This role pays less than
93%
of similar roles. Most pay
$164,250–$223,962
— the shaded band above.
At the midpoint, this role pays about
$124k
versus about
$194k
for comparable roles.
Based on 240 similar postings.
Employer
About Early Warning Services
Early Warning Services is a fintech company that operates the Zelle person-to-person payments network, the Paze digital checkout wallet, and Certos fraud prevention and identity risk solutions for financial institutions.
Early Warning Services currently has
64 open roles
on FindRole.
Listed pay typically runs
$143,500–$183,000
across 60 roles with salary data.
Technical Product Manager - Data joins the Data & AI team to define and deliver next-generation enterprise data platform capabilities. This role focuses on building internal-facing products that enable teams to discover, access, govern, curate, process, deploy, and observe data applications at scale. The primary objective is creating self-service workflows to improve developer productivity and ensure trusted data consumption across analytics, engineering, and business units. Key responsibilities include managing the product roadmap for data ingestion, metadata management, and quality while collaborating with cross-functional teams like Data Engineering and Security. Candidates must possess expertise in modern data platform concepts including pipelines, data lakes, orchestration, and observability. Required skills include SQL, Agile methodologies, and Jira. The role solves complex problems regarding data governance, lineage, and scalability within a highly regulated financial services environment to support robust reporting and decision-making.
What does a Technical Product Manager earn?
Median $165310 from 32 postings across 16 companies.
Execute the product roadmap for enterprise data platform capabilities including ingestion, curation, governance, and observability.
Translate internal user needs from engineers and analysts into technical requirements and product enhancements.
Design and drive adoption of self-service workflows to improve developer productivity and data discovery.
Define and prioritize product requirements to improve platform usability, reliability, and operational efficiency.
Establish success metrics to measure platform performance through adoption, satisfaction, and business impact.
Partner with engineering teams to establish standards, reusable frameworks, and consistent patterns for data pipelines.
Embed data governance, metadata management, and security controls into all platform capabilities and workflows.
Identify opportunities for automation and process improvements across the entire data lifecycle.
What we're looking for
Candidates must independently possess eligibility to work in the United States at the date of hire.
Bachelor's degree in STEM, Computer Science, Information Systems, Engineering, or a related field.
5+ years of experience in Product Management, Data Product Management, Platform Product Management, Data Engineering, Analytics Engineering, or related disciplines.
3+ years of experience working directly with technical teams such as Data Engineering, Platform Engineering, Software Engineering, Analytics Engineering, or Data Architecture.
Experience delivering internal platforms, developer tools, data products, or enterprise technology capabilities.
Working knowledge of SQL and modern data engineering concepts and workflows.
Strong understanding of modern data platform concepts including pipelines, data lakes/warehouses, orchestration, metadata, governance, observability, and data quality.
Master's degree in STEM or related field (preferred); experience in Data Engineering, Analytics Engineering, Software Engineering, or Data Architecture (preferred).
Data Management
AI
Generative AI
Data Quality
Contract Lifecycle Management
Data Governance
Agile
Data Analytics
Data Architecture
Data Integration
AWS
Informatica
Collibra
Talend
Cloud Platforms