Senior Data Developer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Salary

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Company

Equity

Offered From the posting source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Senior Data Developer Montreal, Toronto MaintainX is the world's leading Asset and Work Intelligence platform for industrial and frontline environments. We are a modern IoT-enabled cloud-based tool for reliability, safety, and operations on physical equipment and facilities. MaintainX powers operational excellence for 13,000 businesses including Duracell, Univar Solutions Inc., Titan America, McDonald's, Brenntag, Cintas, Xylem, and Shell. We recently completed a $150 million Series D funding round, bringing our total funding to $254 million and valuing the company at $2.5 billion. We are seeking a Senior Data Developer to join our growing team. You will help build and maintain the data platform that directly powers the MaintainX product and enables internal analytics and BI, while developing platform capabilities and tooling used by software development teams daily. You will contribute across the data platform, including pipelines (batch, micro-batch, and streaming), deployment, governance, and developer tooling. What you'll do: - Build and evolve the Databricks-based data platform used for product features, machine learning, and internal reporting - Design and develop reliable and scalable data ingestion and transformation pipelines - Model raw data into clean, reliable datasets that power both product features and internal analytics - Build platform abstractions and tooling that improve developer experience for data producers and consumers - Improve observability, testing, and monitoring to ensure reliability and performance - Manage and contribute to data governance, security, compliance, and access controls - Contribute to platform standards and architecture as the data platform scales - Collaborate with software development, machine learning, product,

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