Revenue Technology - Data Strategy & Operations Lead

JobsCloseBy Editorial Insights

Mercury is hiring a Revenue Technology Data Strategy & Operations Lead to own the data foundations powering revenue execution, reporting to the Head of Platforms & Infrastructure and partnering with Data Engineering, Data Science, Solution Architecture, and Platform Engineering. You’ll ensure Salesforce and GTM data are reliable, define core data models and contracts, uphold quality standards, monitor pipelines, and reduce manual work while supporting forecasting and lifecycle tracking. Requires 7+ years in data engineering or data systems in SaaS, expert SQL and data modeling, hands-on with Snowflake BigQuery Redshift, ETL/ELT tools, and Salesforce data. Preferred: revenue data, governance, mentoring. Tip: tailor your resume to show end-to-end pipeline ownership and cross-team impact on revenue data integrity.

Mercury is redefining *banking for ambitious companies and behind every great financial platform is a data system that people can actually trust.

As Mercury scales, our revenue systems generate an enormous amount of information: signals from remote and in-person meetings, automation tools, product usage, lifecycle events, and analytics pipelines. Turning that activity into clear, reliable intelligence — without brittle pipelines or constant rework — is critical to how we grow.

We’re looking for a Data Strategy & Operations leader to own the data foundations that power revenue execution. This role ensures that revenue data is reliable, interpretable, scalable, and usable as the business evolves and that teams can act on what they see with confidence.

In this role, you will report to the Head of Platforms & Infrastructure and play a central role in shaping how Mercury models, governs, and operationalizes GTM data. You’ll partner closely with Data Engineering, Data Science, Solution Architecture, Platform Engineering. etc.

*Mercury is a fintech company, not an FDIC-insured bank. Banking services provided through Choice Financial Group and Column N.A., Members FDIC.

Here are some things you’ll do on the job:

• Own the definition, structure, and reliability of data originating from revenue platforms (e.g., Salesforce, GTM tools, automation systems)
• Serve as the primary decision owner for GTM-sourced tables and views used for revenue execution, forecasting inputs, lifecycle tracking, and signal-based workflows
• Design and evolve core GTM data models across Salesforce, ETL, and analytics layers
• Partner with Data Engineering to align GTM schemas with enterprise data models and define clear data contracts between source systems and downstream consumers
• Partner with Data Science / Analytics to ensure revenue data is interpretable, statistically sound, and reflects how the business actually operates
• Own clarity around data ownership boundaries, shared dependencies, and escalation paths when upstream or downstream changes impact revenue integrity
• Define and uphold data quality, freshness, consistency, and documentation standards for revenue platforms
• Monitor and improve pipeline reliability, performance, and scalability, proactively identifying fragile or redundant transformations
• Identify opportunities to automate manual or error-prone data workflows and reduce operational overhead
• Act as a data thought partner to Platforms & Infrastructure, Revenue Operations, Analytics, and Security — advising on feasibility, tradeoffs, and sequencing for data-heavy initiatives

You Should:

• Have 7+ years of experience in data engineering or data systems roles within SaaS or technology companies
• Have deep experience designing and operating production data pipelines
• Be highly proficient in SQL and experienced in data modeling
• Have hands-on experience with modern data stacks (e.g., Snowflake, BigQuery, Redshift)
• Have experience with ETL / ELT tooling (e.g., dbt, Airflow, Census, or similar)
• Understand Salesforce data models and common GTM system architectures
• Be able to translate business concepts into durable, well-structured data models
• Communicate clearly with both technical and non-technical partners

Preferred:

• Experience supporting revenue, sales, or customer lifecycle data
• Familiarity with event-based data platforms (e.g., Data Cloud or equivalents)
• Experience working alongside platform engineering and security teams
• Exposure to data governance, access controls, and compliance considerations
• Experience mentoring or guiding other data practitioners

Compensation:

The total rewards package at Mercury includes base salary, equity, and benefits.

Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate’s experience, expertise, geographic location, and internal pay equity relative to peers.

Our target new hire base salary ranges for this role are the following:

• US employees in New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $158,400 - $198,000
• US employees outside of New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $142,600 - $178,200
• Canadian employees (any location): $149,700 - 187,100 CAD

Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic. We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.

We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on January 22, 2024.

[Please see the independent bias audit report covering our use of Covey for more information.] 

#LI-SN1