Senior Data Engineer

About the role

Super Payments

Super Payments is the only global fintech platform providing 0% processing fees for merchants. Our mission is to use data and AI to make payments free for businesses, so that everyone wins.

At Super, we are disrupting payments, like Spotify did to music and Robinhood did to trading. We don't make money from transaction fees; instead, we monetise through value-added services such as lender commissions and FX. Our platform supports multiple payment methods — from traditional cards to direct bank transfers via open banking, as well as Apple Pay, Google Pay, and our own Buy Now Pay Later solution.

Super has raised $66M from leading investors including Accel, Union Square Ventures and Local Globe (the same investors behind Spotify, Stripe, Monzo) and founded by Samir Desai CBE, co-founder of Funding Circle.

Already trusted by thousands of businesses and more than 4 million customers, Super is processing at a run rate of £1.5B and growing 4x YOY

Our Values

- Customer obsessed: We only succeed when our customers do.

- Move fast: Build, test and improve quickly. Progress matters more than perfection.

- Own it: Be accountable, solve problems, and make it happen.

- Be open: Act with honesty and respect. Transparency builds trust.

- Win together: Collaboration beats ego every time.

Senior Data Engineer

Role Overview

We run an event-driven data platform on AWS and Snowflake. Events flow from our product services through EventBridge, Kinesis Firehose, S3, and are auto-ingested into Snowflake via Snowpipe; batch and third-party data lands through Snowpark-deployed Python procedures. All infrastructure is defined in Terraform/Terragrunt. Python (Poetry, Pydantic, pytest) is our pipeline language; GitHub Actions runs CI/CD. Datadog gives us end-to-end pipeline observability.

Key Responsibilities

Ingestion & Pipeline Engineering

- Event Pipeline Ownership: Build and evolve the EventBridge → Firehose → S3 → Snowpipe ingestion path, including partitioning and throughput tuning as event volumes grow across streams like fraud, payments and merchant.

- Batch & Third-Party Integrations: Design and deploy Snowpark-based Python procedures for file-based and third-party data loads, scheduled and monitored as Snowflake Tasks.

- Schema Evolution: Work with product engineers to manage upstream schema changes and late-arriving data without breaking downstream consumers.

Infrastructure & Reliability

- Infrastructure as Code: Own and extend Terraform/Terragrunt modules for ingestion infrastructure across multiple environments.

- Pipeline Observability: Design Datadog monitors and alerting for Firehose, EventBridge, DLQs and Snowpipe; triage and resolve ingestion failures.

- Security & Compliance: Manage PII handling (hashing, secure deletion), masking, data governance and access in Snowflake. Support audit-ready, reconciled data for Finance and Compliance.