Backend Data Engineer – Lakeflow & Job Development

Backend Data Engineer – Lakeflow & Job Development

New Role

Contract – 6 months and for possible extensions

Remote

Canadian Citizen/Permanent Resident only

Pay Rate: $50-$60 per hr.

Role Overview The Backend Data Engineer is responsible for designing, building, and maintaining scalable data pipelines and backend data workflows. This role focuses on Lakehouse/Lakeflow architectures, job orchestration, and data processing to support analytics, reporting, and downstream applications.

Key Responsibilities Design and implement backend data pipelines using Lakeflow and job orchestration frameworks

Develop, schedule, and monitor batch and streaming data jobs

Build and maintain data ingestion, transformation, and enrichment processes

Optimize data pipelines for performance, reliability, and cost

Ensure data quality, validation, and error handling across workflows

Collaborate with analytics and visualization teams to support reporting needs

Implement logging, monitoring, and alerting for data jobs

Maintain technical documentation for pipelines, jobs, and architectures

Required Skills & Experience Strong experience in backend data engineering and pipeline development

Hands-on experience with Lakehouse / Lakeflow architectures

Proficiency in SQL and at least one programming language (Python, Scala, or Java)

Experience building and scheduling data jobs using orchestration tools

Strong understanding of ETL/ELT patterns and data lifecycle management

Nice-to-Have Skills Experience with Databricks, Spark, Delta Lake, or similar platforms

Familiarity with cloud-native data services (Azure Data Factory, AWS Glue, GCP Dataflow)

Experience with CI/CD for data pipelines

Knowledge of data governance, security, and access control

Success Criteria Reliable, scalable, and well-documented data pipelines

Minimal job failures and efficient recovery processes

Strong collaboration with analytics and reporting teams

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