Senior Data Engineer

Overview

Mesh moves money across hundreds of exchanges, wallets and chains. The data that flow generates is now a product in its own right: clients want to see their conversion, volume and settlement data, Finance needs reporting they can sign, and our own teams answer most questions by asking an AI agent instead of filing a ticket. You'll own how we define, instrument, validate and ship that data, working hands-on in SQL and Python and building the guardrails that let AI agents query our data safely.

What You'll Do

• Own product and client analytics. Define core metrics (conversion rates, transaction success rates) and maintain the central Amplitude data with reusable, templated charts. Build internal and external dashboards for clients.
• Run experiment readouts. Baseline and read out A/B tests on the flow (UI variants, algorithms) and turn results into product decisions.
• Prove migrations with data. Build apples-to-apples comparisons between platforms so decisions move on evidence, not gut feel.
• Guard data integrity. Run and automate daily reconciliation triage and the verification engine.
• Shape instrumentation. Define backend event schemas and the tracking plan, and normalize fields so the data is clean enough for analytics.
• Build finance-grade reporting. Deliver settlement and billing reporting on Microsoft Fabric / Power BI with parity validation, alerting and self-serve access for Finance.
• Make data AI-native. Build skills and tools for our internal data agent, log and audit agent-generated SQL, and keep the self-serve data channels accurate.
• Turn data into client products. Help shape self-serve reporting, reconciliation and billing exports that clients pay for.

Who You Are

• Expert in SQL (T-SQL / SQL Server and Spark SQL a plus) and solid in Python
• Hands-on with product analytics (Amplitude, Mixpanel or similar), including event design and funnel/CVR modeling
• Comfortable with experiment design and statistics for A/B readouts
• Experienced building data quality checks, reconciliations or backfills on production data
• In the habit of validating numbers against source systems before anyone else sees them
• A clear writer who can explain a data issue to an engineer, a CRO and a client in the same day
• A daily user of AI coding and analysis tools
• ~3+ years in analytics or data engineering
• ~5+ years with end-to-end ownership of a data domain.

Pay and benefits

The compensation range provided may span multiple career levels and will be narrowed during the interview process based on factors including a candidate's experience, skills, qualifications, and geographic location. For candidates outside of New York or San Francisco, compensation will be adjusted to reflect the applicable market and location-based pay band.

The base salary range listed excludes commission (if applicable), equity, and benefits. The pay range represents the minimum and maximum target for new-hire compensation. Actual compensation may vary and may be higher or lower depending on individual circumstances.

In-Office Expectations

Employees based in our San Francisco, New York, and Bangalore hubs are expected to work from the office at least 40% of the time (approximately two days per week). This expectation may vary slightly depending on role, team, and business needs. Certain roles that require closer cross-functional collaboration or operational support may have additional in-office requirements, which will be discussed during the interview process.

Our hybrid approach is designed to balance meaningful in-person collaboration, team building, and real-time decision-making with the flexibility to work remotely. We believe this structure supports strong execution while preserving autonomy and focus time.