Senior Data Engineer

Canada
Remote
Posted Oct 14, 2026
1 position

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Employment type: Contract
Experience level: Senior · 5+ years
Posting language: English
Working hours: 40 hours per week
Seniority: Mid-Senior level
Application method: Direct apply is available

Job summary

Design and build analytics-ready data models and production pipelines, including batch and streaming workflows, ingestion, transformation, orchestration, replication, and historical backfills. Test, deploy, validate, and troubleshoot production data solutions while contributing documentation, release materials, code reviews, demonstrations, and knowledge transfer.

Job details

Remote 3-month contract, work to be done in PST hours We are seeking experienced Data Engineers to support the design, development, testing, deployment, and operationalization of analytics-ready data models and associated data pipelines. These engineers will work as an extension of the existing engineering organization and execute work from a jointly prioritized backlog. Key Responsibilities: Design logical and physical data models. Develop analytics-ready Tier-2 data models using dimensional modeling and star-schema principles where appropriate. Define facts, dimensions, relationships, measures, and transformations. Develop ingestion, transformation, and orchestration pipelines. Implement batch and streaming data-processing workflows. Support data replication and historical backfills. Develop data-quality controls and validation logic. Perform unit, integration, regression, and data-quality testing. Reconcile source and target datasets. Prepare production-ready code, configuration, and models. Participate in code reviews and approved release processes. Support production deployment and post-deployment validation. Troubleshoot defects and perform root-cause analysis. Create technical documentation, release notes, and operational materials. Participate in daily stand-ups, design reviews, demonstrations, and knowledge-transfer activities. Required Qualifications: Five or more years of professional data engineering or distributed-systems experience. Strong production experience with batch and streaming data architectures. Experience building and maintaining production data pipelines. Experience with dimensional data modeling and star-schema design. Strong programming skills using Python, Java, and SQL. Experience with data quality, automated testing, and production troubleshooting. Experience with source control, CI/CD, code reviews, and agile engineering practices. Ability to work effectively within a distributed global engineering team. Required Technologies: Apache Iceberg Apache Airflow Apache Spark Apache Kafka Apache Flink Snowflake Java and Python Amazon Web Services SQL and data modeling Expected Deliverables: Completed source code, configurations, and data models. Technical and operational documentation. Approved pull requests. Testing and validation evidence. Engineering demonstrations or technical walkthroughs. Release notes and change summaries. Production deployment artifacts. Post-release validation. Knowledge transfer and documented handoff of remaining work.

What you’ll do

Requirements

Requires at least five years of data engineering or distributed-systems experience, with production experience in batch and streaming architectures and data pipelines. Candidates should be proficient in Python, Java, and SQL, and have experience with dimensional modeling, data quality, automated testing, production troubleshooting, CI/CD, source control, code reviews, and agile practices.