Full-Time

Senior Product Manager

Structured Finance

Prophecy

Prophecy

51-200 employees

Low-code data engineering for Spark/Airflow

No salary listed

Remote in USA + 2 more

More locations: San Francisco, CA, USA | New York, NY, USA

Remote

Category
Product
Required Skills
LLM
BigQuery
Apache Spark
SQL
Machine Learning
Databricks
Snowflake

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Requirements
  • 5+ years of product management experience in data platforms, analytics products, or financial technology
  • Strong understanding of structured finance concepts and workflows, e.g. ABS, MBS, CLOs, etc.
  • Experience working closely with engineering teams to deliver technical products
  • Experience working with complex, data-intensive systems
  • Ability to translate domain-specific problems into clear product requirements
  • Strong communication skills, with the ability to simplify complex financial and technical concepts
  • Experience operating in a high-growth startup environment (Series A–C)
  • Experience working in or with investment banks, asset managers, fintechs, or structured finance platforms as well as loan-level datasets, cash flow models, or risk systems
  • Familiar with modern data infrastructure, e.g. Snowflake, Databricks, BigQuery, Spark, SQL
  • Experience building or shipping AI/ML-powered features in regulated environments
  • Comfort using AI tools (LLMs, copilots) to accelerate product thinking and prototyping
Responsibilities
  • Own and evolve the roadmap for a product area over a 1–3 quarter horizon, balancing customer needs, technical investments, and business goals
  • Define how capabilities such as data preparation, modeling, and analytics come together into cohesive systems
  • Make thoughtful trade-offs across customer needs, technical constraints, and business impact
  • Think in systems: how does the product support the full lifecycle from asset ingestion to reporting and decisioning
  • Develop deep understanding of structured finance workflows, including asset-backed securities (ABS), MBS, CLOs, or similar instruments, loan-level data ingestion and normalization, cash flow modeling and scenario analysis, tranche structuring and risk analysis, amd regulatory and investor reporting
  • Engage directly with customers (banks, asset managers, fintechs) to uncover constraints, inefficiencies, and unmet needs
  • Frame complex financial and operational problems into clear, actionable problem statements
  • Use AI tools (LLMs, copilots, workflows) as a core part of product development, not an afterthought
  • Build lightweight prototypes (prompts, workflows, internal tools) to validate ideas before writing full specifications
  • Identify where AI-driven capabilities and automation can meaningfully improve user workflows
  • Ensure AI features are reliable, explainable, and aligned with enterprise requirements
  • Work closely with engineering and design to deliver high-quality product capabilities
  • Write clear, structured product specifications grounded in data and user insight
  • Define success metrics and track adoption, impact, and effectiveness
  • Monitor execution progress, identify risks early, and drive cross-team alignment
  • Maintain a high bar for usability, reliability, and product integrity
  • Align engineering, design, sales, and customer success around shared outcomes
  • Communicate product direction through clear documentation and structured decision-making
  • Resolve ambiguity and misalignment quickly to maintain execution momentum
  • Contribute to product positioning and narrative through artifacts such as one-pagers, demos, and customer-facing materials
  • Own the operational health of your product area, including performance monitoring, feature adoption, issue triage, and iteration cycles
  • Establish and improve repeatable processes that increase execution speed and predictability
Desired Qualifications
  • Experience operating in a high-growth startup environment (Series A–C)
  • Experience working in or with investment banks, asset managers, fintechs, or structured finance platforms as well as loan-level datasets, cash flow models, or risk systems
  • Familiar with modern data infrastructure, e.g. Snowflake, Databricks, BigQuery, Spark, SQL
  • Experience building or shipping AI/ML-powered features in regulated environments
  • Comfort using AI tools (LLMs, copilots) to accelerate product thinking and prototyping

Prophecy.io is a low-code data engineering platform that helps data teams build and manage Spark workflows and Airflow schedules. It offers a visual interface for designing jobs and schedules, plus metadata search and column-level lineage for governance. It targets medium to large enterprises and uses a subscription-based model for access to its toolkit. Its goal is to speed up development and improve reliability and observability of data pipelines.

Company Size

51-200

Company Stage

Series B

Total Funding

$116.5M

Headquarters

San Francisco, California

Founded

2017

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See people who can refer or advise you

Simplify Jobs

Simplify's Take

What believers are saying

  • The January 16, 2025, $47 million Series B1 extends runway and credibility.
  • Prophecy's July 2026 Snowflake and BigQuery fabric support widens its addressable platform footprint.
  • Free accounts and InfoWorld's January 6, 2026 award increase inbound demand and trial conversion.

What critics are saying

  • Databricks, Snowflake, and BigQuery can copy Prophecy's workflow layer and crush pricing by 2027.
  • Alteryx, dbt, and Fivetran already own adjacent budgets, slowing Prophecy's enterprise sales cycles.
  • If AI workflow generation disappoints audits, Prophecy becomes another demo product, not infrastructure.

What makes Prophecy unique

  • Prophecy v4, launched February 24, 2026, turns prompts into inspectable workflows.
  • Native execution on Databricks, Snowflake, and BigQuery keeps workflows governed and portable.
  • Git-stored production code and column-level lineage separate Prophecy from black-box AI copilots.

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Benefits

Health Insurance

Unlimited Paid Time Off

Wellness Program

Professional Development Budget

Company Equity

Life Insurance

FSA/HSA

Long Term Disability

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

2%

2 year growth

1%
PR Newswire
Feb 24th, 2026
Prophecy launches v4 with AI agents for visual data prep on Databricks, Snowflake and BigQuery

Prophecy has launched v4, an AI data preparation and analysis platform that uses AI agents to convert business requirements into visual data workflows. The platform generates inspectable workflows that run natively on Databricks, Snowflake and BigQuery. The system addresses validation challenges in AI-generated data logic by making outputs visual and reviewable, rather than requiring users to check lengthy SQL or Spark code. Workflows are stored as production-grade code in Git and inherit governance policies from underlying data platforms. Prophecy v4 aims to replace legacy desktop tools by combining AI-driven productivity with cloud-native execution. The platform unifies data analysis steps into a single interface where users can iteratively refine results through conversational interactions with agents whilst maintaining synchronisation between visual workflows and code. The platform is available now with free accounts offered.

Tabor Communications Inc.
Mar 28th, 2025
Prophecy 4.0 Offers Fully Governed Self-Service Data Prep for Databricks SQL

Additionally, Prophecy has introduced built-in automation with a drag-and-drop interface.

Prophecy
Jan 20th, 2025
Prophecy takes in $47M to scale-up and re-imagine data integration with AI

I’m pleased to share that Prophecy today announced a $47M Series B1 round. Smith Point Capital led the round, with HSBC joining as a new investor and participation from existing investors including Berkeley SkyDeck, DallasVC, Insight Partners, JPMorgan Chase and SignalFire.

FinSMEs
Jan 16th, 2025
Prophecy Raises $47M in Series B Extension Funding

Prophecy raises $47M in Series B extension funding.

SiliconANGLE Media
Jan 16th, 2025
Prophecy raises $47M for AI data pipelines

Prophecy Inc., a data copilot startup, raised a $47M Series B extension led by Smith Point Capital, with participation from HSBC and others. The company uses generative AI to automate data pipeline development, making data accessible across systems. Prophecy's copilot, integrated with Databricks, accelerates AI initiatives by simplifying data preparation. The funding will enhance its platform and expand its customer base by 2025.