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Senior Software Engineer, Recognition & DataCore Team

Lansweeper - Rome, Lazio, Italy

Posted May 27, 2026

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
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Market context

U.S. role benchmark (BLS OEWS)
$111,944 U.S. median for this role
Projected growth (BLS Employment Projections)
+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

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

Schedule

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Weekend work
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Application

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Deadline
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About this role

Senior Software Engineer, Recognition & DataCore Team Rome, Lazio, Italy Senior Software Engineer Location: Rome, Italy Hybrid: 2-3 days a week in office Context & Impact We're looking for a Senior Software Engineer to join our Recognition & DataCore Team in Rome, Italy . This role sits within a high-performing engineering group tackling some of the most complex challenges in cloud-scale data infrastructure - designing and maintaining the cloud-native data pipeline engine that powers the Lansweeper platform. You won't just be maintaining systems; you'll be shaping how AI and intelligent automation transform the way we process, enrich, and reconcile massive datasets at scale. Your work will directly impact how Lansweeper ingests, processes, and delivers actionable technology asset intelligence across customer environments worldwide. Engineers here operate at the intersection of distributed systems and AI-augmented engineering - where the quality of your judgment matters as much as the quality of your code. In the short term, you'll drive the evolution of our distributed data pipeline. Long term, you'll contribute to architecture decisions, next-generation data processing capabilities, and the scalability of a platform trusted by thousands of enterprises globally. Challenge The main challenges you'll face are: - Enhancing and maintaining a high performance data pipeline for Lansweeper Discovery and the broader Lansweeper Platform - Solving complex ETL, enrichment, and data reconciliation problems at scale with AI tooling as a force multiplier, not a shortcut - Operating effectively within a large-scale distributed architecture where performance, reliability, and engineering excellence are non-negotiable - Setting the

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