Senior Data Engineer

San Francisco, California, United States · On-site

About this role

Senior Data Engineer

Overview

Tilia is hiring a Senior Data Engineer to transform raw platform activity into key data for business insights, financial reporting, and regulatory reporting. Tilia is a licensed money transmitter powering digital economies for well-known virtual worlds, games, and creator platforms. We move millions of dollars between real-world currency and in-game tokens and we have to account for every penny of it, and Data Engineering is where the magic happens. We're a Python and SQL shop on BigQuery and AWS, currently building a new data lake on S3 and Athena. Success means reliable, accurate pipelines that finance, compliance, and analysts can trust, and reports that hold up under audit. This role reports to the VP of Engineering.

The Role

As a Senior Data Engineer, you'll spend most of your time building and operating ETL while also operating and extending our data infrastructure. This is a hands-on individual contributor role with real ownership and genuine influence over how Tilia's data architecture evolves.

Day-to-day responsibilities:

  • Build, extend, and debug ETL jobs, testing and validating locally before deploy
  • Build the SQL transformations that turn production data into the curated datasets the business runs on
  • Help execute our migration to a new AWS data lake on S3 and Athena, fed by DMS, without breaking what's live
  • Calculate charges and earnings for our customers and their content creators, generate traceable invoices, and reconcile settlements
  • Produce US money-transmitter reporting on outstanding stored value and money transmission liability
  • Model new data, carefully weighing partitioning, indexing, and data types
  • Write data validations to ensure high quality reporting
  • Investigate pipeline failures, find the root cause, and fix it
  • Partner with backend engineers on schema changes, keeping pipelines in step with a changing production environment
  • Translate finance and compliance requirements into pipelines and data models
  • Work with analysts and product to build the data behind key business and publisher reporting metrics

Key stakeholders:

  • Internal: your data team, backend engineering, analysts, product, finance, and compliance
  • External: publishers who rely on our reporting, and our payment and banking data partners

Tech stack:

Python, SQL, Airflow, BigQuery, MySQL, Change Data Capture, and AWS data services including S3, Athena, and DMS.

Success in this role means:

  • Reliable, accurate pipelines that finance, compliance, and analysts can trust
  • Financial and regulatory reports that hold up under audit
  • A clean cutover to the new AWS data lake without disrupting live reporting

Location: On-site in San Francisco, CA.

Travel: Some travel required for periodic team offsites.

Knowledge Required

Qualifications

A Bachelor's degree in Computer Science or a related field is preferred, though equivalent professional experience is equally valued. No specific certifications are required.

Experience

A proven track record building and operating production data pipelines and warehouses.

Technical skills:

  • Expertise with RDBMS and SQL, including window functions, complex joins, aggregation, query optimization, and index design
  • Python proficiency for building and maintaining ETL code, including testing
  • Production data-warehouse experience with BigQuery, Snowflake, Redshift, or similar, modeling and transforming data at scale rather than just querying it
  • Workflow orchestration experience with Airflow or a comparable tool such as Dagster, Prefect, or Luigi
  • Hands-on experience with AWS data and analytics services such as S3, Athena, and DMS
  • A correctness-first instinct for financial data: you build for auditability and reconcile rather than assume

Leadership and collaboration:

  • Clear, effective communication of data trade-offs to both technical and non-technical stakeholders
  • Ability to explain to finance, compliance, and analysts what the data does and doesn't say

Industry background, preferred but not required:

  • Payments or fintech data experience
  • Regulatory or compliance reporting experience: money transmission, tax, SOC-2, or PCI
  • Background in virtual economies, gaming platforms, or creator economy products

Nice to have:

  • Change Data Capture experience with Maxwell, Debezium, or AWS DMS
  • Experience with metadata-driven or config-driven ETL frameworks
  • Go literacy, enough to read the backend services that produce your source data
  • Experience building reporting for non-engineering consumers in Tableau, Looker, or similar

Company at a glance

Thunes is the Smart Superhighway to move money around the world. Thunes’ proprietary Direct Global Network allows Members to make payments in real-time in over 140 countries and more than 90 currencies. Thunes’ Network connects directly to over 12 billion mobile wallets, stablecoin wallets and bank accounts worldwide, as well as 15 billion cards via more than 220 different payment methods, such as GCash, M-Pesa, Airtel, MTN, Orange, JazzCash, Easypaisa, AliPay, WeChat Pay and many more.

Thunes’ Direct Global Network differentiates itself through its worldwide reach, in-house SmartX Treasury System and Fortress Compliance Platform, ensuring Members of the Network receive unrivaled speed, control, visibility, protection, and cost efficiencies when making real-time payments, globally.

Members of Thunes’ Direct Global Network include gig economy giants like Uber and Deliveroo, super-apps like Grab and WeChat, MTOs, fintechs, PSPs and banks.

Headquartered in Singapore, Thunes has offices in 14 locations, including Atlanta, Barcelona, Beijing, Dubai, Hong Kong, Johannesburg, London, Manila, Nairobi, Paris, Riyadh, San Francisco, Sao Paulo and Shanghai.

For more information, visit: https://www.thunes.com/

Founded2016
Team Size501-1,000 employees
WorkspaceOn-site
IndustryFinancial Services
Location
San Francisco, California, United States
Websitethunes.com
LinkedInLinkedIn

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