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Senior Data Engineer

Flinks•Canada•🌍 Remote
Full-time3-7
CAD 120K - CAD 160K
per year
👁️ 0 views•📝 0 applications•Posted 9/6/2026•Expires 11/5/2026
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Job Description

About Flinks Flinks is the embedded finance platform that brings together connectivity, intelligence, and payments — giving businesses the infrastructure they need to build and deliver seamless financial experiences at scale.

As a leader in Open Finance in Canada, we’ve grown since 2016 into one of North America’s most trusted platforms for financial data access, enrichment, and money movement. We work with innovators across many industries, including lending, fintech, banking, insurance, and wealth management.

Today, our platform connects to 15,000+ financial institutions across North America and powers over 1M monthly connections. We also give our customers unprecedented visibility into 4,500+ real-time financial insights to support smarter decisioning.

Companies rely on Flinks to streamline onboarding, verify income, assess credit risk, and power faster payment experiences. We’re on a mission to drive financial innovation and help businesses build financial experiences that feel effortless, connected, and customer-first. That’s where you come in.

The Role We're hiring our Senior Data Engineer (Data / ML Platform) to stand up data engineering as a discipline at Flinks .

You'll own the data and ML platform that turns models into reliable production services, harden the data models the business runs on and close the seam between our data scientists and the product teams. This is a high-ownership, greenfield-leaning role: much of this foundation is yours to build and own, not inherit.

If you like being the person who makes data and ML production-grade - pipelines, serving, governance, reliability - and you want broad impact across a company's data, this is built for you.

What You'll Do

Own and evolve the data platform - the BigQuery warehouse, dbt transformation layers, Airflow / Cloud Composer orchestration and Pub/Sub ingestion that feed every model and metric. Build and operate the ML platform - training pipelines (Kubeflow on Vertex AI), model serving (FastAPI be

Required Skills

BigQuerydbtAirflowCloud ComposerPub/SubKubeflowVertex AIFastAPI

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