lever
Senior Data Engineer
Nimblerx
Toronto, CAN
Full-time
Senior · 5+ years experience
Hybrid
CAD 175000-230000 yearly / year
Discovered 3 weeks ago
PythonPySparkSQLJavaSpring BootSpark
Free
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PythonPySparkSQL
Key Skills for This Role
PythonPySparkSQLJavaSpring BootSpark
Full Job Posting
- Own the data platform end-to-end — ingestion, transformation, storage, query, and access — and drive its roadmap as the company's data needs grow
- Build and evolve batch and streaming pipelines on PySpark/EMR, Kinesis, Lambda, and Step Functions, ingesting from Postgres, Salesforce, third-party vendors, and product event streams into our Iceberg-based lake
- Model the warehouse: design SCD tables, event tables, and the conventions other engineers and analysts follow when adding new data
- Partner with product, engineering, analytics, and operations stakeholders across the company to turn data requests into well-scoped, reliable pipelines — and write the docs and tooling that let them self-serve next time
- Own the security and compliance backbone of our data systems, including audit logging, access control, and temporary-access workflows
- Optimize backend query performance where the data layer meets product code — reader-replica routing, indexing, caching, and IO instrumentation in our Java/Spring services
- Lead investigation and remediation when data infrastructure misbehaves — IOPS spikes, pipeline failures, schema drift, late data — and make the fixes durable
- Use AI as a daily accelerant for pipeline scaffolding, schema work, and ad-hoc investigations — and ship internal AI tooling that lets other teams do the same
- Mentor engineers and analysts across the company on how to work with the data platform
- 5+ years of experience building production data pipelines and platforms
- Deep Python (PySpark) and SQL fluency, including tuning Spark jobs at scale
- The skills and willingness to work on the services around the data layer (Java, Spring Boot)
- Hands-on experience with distributed compute (Spark/EMR), streaming (Kinesis), and object storage (S3)
- Solid Postgres fundamentals — query optimization, indexing, replication, replica routing, and a feel for when the database is the bottleneck
- Experience with Iceberg and Trino, or similar
- Comfort with CI/CD and Terraform
- Already building with AI — frontier models, agentic coding tools, or something you hacked together last weekend
- Track record of working across teams that don't speak your language (product, ops, etc.)
- You take ownership of the platform's reliability, cost, accessibility, and compliance — not just the tickets you happened to ship
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