Senior Staff Software Engineer - Data Platform

Marqeta•Vancouver, BC

1d•CA$177,100 - CA$221,400•Remote

About The Position

This is a software engineering role on a software engineering team. The team builds and operates the data platform: the infrastructure, abstractions, and SDKs that the rest of Marqeta's data and ML organization runs on. We are not writing pipelines–we are building the platform pipelines run on. If you've spent your career building infrastructure that other engineers depend on; and you know the difference between “software engineering” and "data engineering", read on. We work Flexible First. This role can be performed remotely anywhere within the United States or from our Oakland office. We’d love for you to join us! Learn more about our Product and Engineering team. At Marqeta, participation in a rotational on-call pager duty is a required part of the software engineering role. The specifics of the rotation may vary by team, depending on team size and structure, and will be discussed further during the interview process.

Requirements

A career building data platforms, not just pipelines.
Demonstrated ability to name abstractions designed, the teams that adopted them, and the problems they solved.
Experience where most of the last several years has been writing transformations rather than building the system transformations run on is not the right fit.
Production depth in modern lakehouse work (Iceberg or Delta in production).
Strong fluency in the surrounding stack: AWS data services (S3, Glue, EMR), Spark, Airflow, Kafka, IAM boundaries for multi-tenant data access.
Mastery of Python in a production data-platform context.
Credible depth in Go or Java.
Understanding of Python idioms, ecosystem, and performance characteristics at scale.
Ability to adopt the best tool for the job.
A track record of evolving live infrastructure.
Experience leading at least one major platform transition end-to-end.
Influence as a working skill.
Ability to build alignment across platform, security, and consumer teams.
Ability to write design docs and RFCs people actually read.
Ability to hold a strong technical position and update on evidence.
A history of growing other engineers — including peers at your level.

Nice To Haves

Payments or fintech context (PCI-DSS, SOX, SOC 2).
CDC tooling experience (Debezium, Kafka Connect).
Data governance tooling (DataHub, Amundsen, Collibra).
Public technical writing or open-source contributions to data infrastructure.

Responsibilities

Build and operate the data platform: the infrastructure, abstractions, and SDKs that the rest of Marqeta's data and ML organization runs on.
Build the platform pipelines run on.
Own the lakehouse and the streaming ingestion that feeds it.
Set the multi-year technical direction.
Design the golden paths.
Ship the work — directly, with your hands on the code that matters.
Own technical direction, application architecture, and the engineering bar.
Write production code on the platform's hardest problems.
Own the design and build of new abstractions end-to-end.
Lead design reviews.
Set the engineering bar through the work itself.
Prototype.
Deep dive on a tricky migration.
Pair with engineers on tough problems.
Build out the lakehouse — the patterns Marqeta will run on for years.
Develop new abstractions and new tooling.
Create the paved road internal teams want to use.
Evolve and harden the platform that's already in production.
Improve reliability, performance, and developer experience without disrupting the teams who depend on it.
Ensure testing confidence and release velocity.
Participate in on-call rotations and blameless postmortems.
Evolve live infrastructure.
Improve reliability, performance, and DX on systems that real teams depend on, sequenced so the work doesn't disrupt them.
Own major platform transitions, including build vs. buy decisions, migration design, risk management, and delivery.
Build alignment across platform, security, and consumer teams.
Write design docs and RFCs.
Grow other engineers — including peers at your level.