Senior Data Engineer

Swoop

. Own the data platform end-to-end, including ingestion, transformation, storage, query, and access .

Posted 10/6/2026full-timeToronto • CanadaSenior💰 CA$195,000 - CA$228,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and optimizing data platforms, including ingestion, transformation, and storage, while ensuring security and compliance. Proficient in leveraging AI for pipeline development and mentoring teams on data platform best practices.

Highest-signal resume keywords

Data Pipeline DevelopmentPython (PySpark) FluencySQL Query OptimizationDistributed Compute (Spark/EMR)Security and Compliance Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data IngestionData TransformationBatch and Streaming PipelinesPostgres FundamentalsAI Tooling DevelopmentSchema DesignJava ProgrammingSpring BootCI/CD PracticesTerraform

Soft Skills

CollaborationMentoringDocumentation WritingProblem SolvingStakeholder Engagement

Tools & Technologies

KinesisLambdaStep FunctionsIcebergTrinoS3EMR

Industry Keywords

Data Platform RoadmapAudit LoggingAccess ControlTemporary-Access WorkflowsPII/PHI Handling

Tech Stack

Tools & technologies

JavaPostgresPySparkPythonSparkSpringSpring BootSpringBootSQLTerraform

About the role

Key responsibilities & impact

Own the data platform end-to-end, including ingestion, transformation, storage, query, and access
Drive the data platform roadmap as company data needs grow
Build and evolve batch and streaming pipelines using PySpark/EMR, Kinesis, Lambda, and Step Functions
Ingest data from Postgres, Salesforce, third-party vendors, and product event streams into an Iceberg-based lake
Design SCD tables, event tables, and data conventions for engineers and analysts
Partner with product, engineering, analytics, and operations stakeholders to turn data requests into reliable pipelines
Write documentation and tooling enabling self-service by other teams
Own security and compliance systems, including audit logging, access control, and temporary-access workflows
Optimize backend query performance through read-replica routing, indexing, caching, and I/O instrumentation in Java/Spring services
Lead investigation and remediation of IOPS spikes, pipeline failures, schema drift, and late data
Use AI for pipeline scaffolding, schema work, and ad-hoc investigations
Ship internal AI tooling for other teams
Mentor engineers and analysts on working with the data platform

Requirements

What you’ll need

5+ years of experience building production data pipelines and platforms
Deep Python (PySpark) and SQL fluency, including tuning Spark jobs at scale
Skills and willingness to work on Java and Spring Boot services around the data layer
Hands-on experience with distributed compute (Spark/EMR), streaming (Kinesis), and object storage (S3)
Solid Postgres fundamentals, including query optimization, indexing, replication, replica routing, and database bottleneck identification
Experience with Iceberg and Trino, or similar
Comfort with CI/CD and Terraform
Experience building with AI, frontier models, or agentic coding tools
Track record of working across product, operations, and other teams
Current Canadian work authorization strongly preferred
Willingness to work on security and PII/PHI handling as core engineering responsibilities

Benefits

Comp & perks

Professional growth opportunities
Hybrid work arrangement
Visa sponsorship may be considered on an exceptional basis for highly qualified candidates with specialized skills