Backend Data Engineer – Lakeflow & Job Development

Buchanan Technologies; Canada; Remote; CAD 68,880 - 82,656; Full time

Job summary

A Canadian tech company is seeking an experienced Backend Data Engineer for a 6-month contract, focusing on designing and maintaining data pipelines using Lakeflow architectures. The role is remote and requires deep expertise in backend data engineering, SQL, and a programming language like Python or Scala. Candidates must be Canadian citizens or permanent residents. Join us to optimize data workflows and support analytics needs in a collaborative environment.

Qualifications

• 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).

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.

Skills

Backend data engineering

Lakehouse architectures

SQL

Python

ETL patterns

Tools

Databricks

Spark

Azure Data Factory

AWS Glue

Job description

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