Finix

Senior Data Engineer

Finix  •  San Francisco, CA (Onsite)  •  1 month ago
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Job Description

About UsMove money. Make money. Finix is a full-stack acquirer processor, empowering businesses of all sizes with flexible, modern payment solutions. Processing billions of dollars annually, Finix enables SaaS, marketplace, and e-commerce platforms to accept payments, manage payouts, and onboard merchants seamlessly. With our no-code, low-code, and developer-friendly tools, businesses can get up and running in hours—not months.
Finix has raised over $175M, including a $75M Series C led by Acrew Capital, with participation from Lightspeed Venture Partners, Leap Global, American Express Ventures, Bain Capital Ventures, Homebrew, Inspired Capital, Sequoia Capital, Visa, and others.
About the Role Finix’s reporting cluster is the source of truth for operational metrics, customer-facing reports, billing, actionable insights, and a host of business-critical KPIs. As a Data Engineer in the Data Engineering team, you will own the tooling, frameworks, data pipelines, integrations, databases, schemas and the data integrity of this cluster. You are critical to both Finix, and our customers, in supplying the data that underpins key operations decisions, uncovers hidden issues, and powers insight through reports, analytics, and dashboards owned and managed by the Data Engineering team. Our operations teams will depend on you to find, source, prepare and supply the right data allowing them to run Finix. Our product team will depend on you to serve the right data quickly and reliably to our customers so they can make timely business decisions. Data Analysts will rely on you to source and channel data where it needs to be and how it needs to be organized to power daily operations and decisions.

You will

  • Enable our operations team to make data-driven decisions based on timely, consistent, complete, and correct data, reports, and analytics
  • Work closely with engineering team members to build reporting and analytics infrastructure, solving our and our customer’s analytics needs
  • Delight our customers by providing leading reporting and analytics capabilities supporting their operations and accounting teams
  • Be the subject matter expert in all things data pipelines, data lakes and warehouse, tooling & frameworks, integration and sourcing of data
  • Design, build and maintain all code, pipelines, schemas, databases and frameworks that power Finix’s data analytics and reporting capabilities

You are

  • Detail-oriented, with a healthy dose of mistrust, driving you to investigate even the slightest data discrepancy
  • Thrive in a fast-paced environment around common goals and priorities but able to self-direct and problem solve with others to make progress
  • Fast learner of new languages, tools & frameworks. You are willing to go wherever necessary to accomplish your goals even if you haven’t been there before. 
  • Curious about new approaches and pushing the boundaries of what exists.

You have

  • 6+ years of experience in a Data Engineering, ETL, Data Science or related role
  • Expert knowledge of SQL, data modeling, Python and frameworks such as Spark, Storm, Airflow, Glue etc. Java would also be great
  • B.S in computer science, mathematics, statistics, physics, or a related data field
  • Experience with BI tools such as Looker, Sisense, Superset, Tableau
Finix

About Finix

Finix is a payment processor that makes it easy for software platforms, marketplaces, and individual businesses of all sizes to accept payments and send money while maximizing revenue and reducing costs.

Finix is trusted by startups and publicly traded companies alike to build and scale their payments infrastructure. Headquartered in San Francisco, Finix is a privately held company with funding from American Express Ventures, Bain Capital Ventures, Homebrew, Inspired Capital, Lightspeed Venture Partners, Sequoia Capital, Visa, and more.

Industry
Finance & Insurance
Company Size
201-500 employees
Headquarters
San Francisco, California
Year Founded
2015
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