Senior Data Engineer
London
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
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- Unconfirmed
What you’ll work on
Full postingWe run an event-driven data platform on AWS and Snowflake.
Support audit-ready, reconciled data for Finance and Compliance.
From the employer’s posting
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.
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. Data Pipelines & Data Quality
What you’ll bring
All qualificationsCore experience
- Python Coding: Python skills for pipeline and infrastructure code (typed models, testing, CI-deployed services), not just scripting or analysis.
- Ownership & Initiative: A strong willingness to work independently, take initiative, and take full ownership of the pipelines and infrastructure you build, from design and implementation through to production reliability.
Qualification wording
Python Coding: Python skills for pipeline and infrastructure code (typed models, testing, CI-deployed services), not just scripting or analysis.
Ownership & Initiative: A strong willingness to work independently, take initiative, and take full ownership of the pipelines and infrastructure you build, from design and implementation through to production reliability.
Tools in this posting
- Python
- SQL
- AWS
- Datadog
- dbt
- S3
- Snowflake
- Terraform
Source — Tool mentions in context
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
- 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.
- Snowflake & Warehouse Engineering: Strong SQL for Snowflake, including Snowpipe, Tasks and Snowpark. - Dbt: Proven experience in building well tested SQL and python models in dbt. - CI/CD & Data Security: Experience with GitHub Actions (or equivalent), and secrets/key management, PII and sensitive data handling in Snowflake.
- CI/CD & Data Security: Experience with GitHub Actions (or equivalent), and secrets/key management, PII and sensitive data handling in Snowflake. - Python Coding: Python skills for pipeline and infrastructure code (typed models, testing, CI-deployed services), not just scripting or analysis. Engineering Ownership
- Infrastructure as Code: Terraform experience required; Terragrunt a plus. Comfortable owning modules across environments, not just consuming them. - Snowflake & Warehouse Engineering: Strong SQL for Snowflake, including Snowpipe, Tasks and Snowpark. - Dbt: Proven experience in building well tested SQL and python models in dbt.
We'd love it if you have - AWS & Event-Driven Architecture: Hands-on experience with streaming/event ingestion (Kinesis, EventBridge or equivalents), S3 partitioning, and queue/DLQ patterns. - Infrastructure as Code: Terraform experience required; Terragrunt a plus. Comfortable owning modules across environments, not just consuming them.
- 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.
Data Pipelines & Data Quality - Dbt: Build privacy-first data pipelines using dbt and Snowflake Dynamic Tables to safely expose sensitive data for downstream analytics and reporting. - Data Quality: Build testing and monitoring for ingestion and transformation logic to catch issues before they reach the business or the Analytics Engineering team.
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.
- 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. Data Pipelines & Data Quality
- Dbt: Proven experience in building well tested SQL and python models in dbt. - CI/CD & Data Security: Experience with GitHub Actions (or equivalent), and secrets/key management, PII and sensitive data handling in Snowflake. - Python Coding: Python skills for pipeline and infrastructure code (typed models, testing, CI-deployed services), not just scripting or analysis.
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.
- AWS & Event-Driven Architecture: Hands-on experience with streaming/event ingestion (Kinesis, EventBridge or equivalents), S3 partitioning, and queue/DLQ patterns. - Infrastructure as Code: Terraform experience required; Terragrunt a plus. Comfortable owning modules across environments, not just consuming them. - Snowflake & Warehouse Engineering: Strong SQL for Snowflake, including Snowpipe, Tasks and Snowpark.
Job description
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.
Data Pipelines & Data Quality
- Dbt: Build privacy-first data pipelines using dbt and Snowflake Dynamic Tables to safely expose sensitive data for downstream analytics and reporting.
- Data Quality: Build testing and monitoring for ingestion and transformation logic to catch issues before they reach the business or the Analytics Engineering team.
- Stakeholder Collaboration: Partner with the wider Engineering team and Analytics Engineering team as a downstream consumer, to ensure pipelines deliver accurate, audit-ready data.
Requirements
We'd love it if you have
- AWS & Event-Driven Architecture: Hands-on experience with streaming/event ingestion (Kinesis, EventBridge or equivalents), S3 partitioning, and queue/DLQ patterns.
- Infrastructure as Code: Terraform experience required; Terragrunt a plus. Comfortable owning modules across environments, not just consuming them.
- Snowflake & Warehouse Engineering: Strong SQL for Snowflake, including Snowpipe, Tasks and Snowpark.
- Dbt: Proven experience in building well tested SQL and python models in dbt.
- CI/CD & Data Security: Experience with GitHub Actions (or equivalent), and secrets/key management, PII and sensitive data handling in Snowflake.
- Python Coding: Python skills for pipeline and infrastructure code (typed models, testing, CI-deployed services), not just scripting or analysis.
Engineering Ownership
Technical Communication: A pragmatic, systems-level mindset with the ability to explain pipeline failures, infrastructure trade-offs, or data-flow issues clearly to both engineers and non-technical stakeholders.
- Ownership & Initiative: A strong willingness to work independently, take initiative, and take full ownership of the pipelines and infrastructure you build, from design and implementation through to production reliability.
- Production Mindset: Proactively monitoring, debugging, and improving pipelines and infrastructure in production, not just building them and moving on.
*The stated experience and background is a guide and does not preclude applications from candidates with more or less experience, provided the requisite skills can be demonstrated.
Our Benefits - here’s a few and more to come ….
- Tax advantage Share Options
- Flexible working model
- Work from home set up
- Learning & Development opportunities
- Contributory Pension Scheme
- Free Team lunch (Tues & Thurs) and social evenings
- Comprehensive PMI & x4 Life Insurance
- Your birthday off, plus one Revival day
If you are excited about sharing the adventure, joining a growing team with big ambitions and you are really great at what you do, then apply now!
Super Payments is an equal opportunity employer, embracing diversity in all its forms and fostering an inclusive environment. The company will not unlawfully discriminate on grounds of gender, sexual orientation, marital or civil partner status, gender reassignment, race, religion or belief, colour, nationality, ethnic or national origin, disability or age, neurodiversity status, pregnancy or trade union membership.
Please let us know if you require any reasonable adjustments at any point during the application and/or recruitment process.
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Source & posting history
Source notes
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- Pay
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- Location & working pattern
London
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- Status in our records
- Active
- First seen by us
- Sep 24, 2026
- Recorded sightings
- 4
- Last seen by us
- Oct 4, 2026
- Employer says posted
- Sep 8, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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