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Added 2 mins ago
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Lasso Informatics

Senior Data Operations Specialist

Montreal, QC, Canada

Job type: Full-time
Apply by: Mar 29, 2027
Posting language: English
Posted: Sep 30, 2026

Apply About employer

Applications open in a new tab.

Original job description

About Lasso Informatics

Research data is wild. It pours in from brain scans, genome sequencing, EEG and eye-tracking, biospecimens and wearables that track sleep and movement, across dozens of sites and years of study. Lasso Informatics ropes it in: our platform pulls it all into one place so researchers around the world can stop fighting with their data and get to discoveries faster.

That is where our name comes from. A lasso brings something wild under control, and that is the job. The people who do it are Wranglers, and we are quite choosy about who earns the title. Wranglers expect a lot of themselves, make everyone around them better, and never stop learning. We move fast, we have fun, and we keep the bar high.

What We Offer

A flexible, hybrid or remote position
Competitive compensation and benefits
Work that matters, with real world scientific and clinical impact
Variety that keeps it interesting: no two studies, pipelines, or releases look the same
Room to grow with a scaling mission-driven company at the forefront of research data management
A sharp, multidisciplinary team that is good at what it does and good to work with.

Remote/Hybrid (Remote: US, Hybrid: Minneapolis / Remote: Canada, Hybrid: Montreal)

Full-Time

Canada Range: $74,000 - $95,000 CAD

US Range: $81,000 - $105,000 USD

Want to Be a Wrangler? Here's What We Look For

You hold yourself to a high standard and bring real technical rigor to your work
You make the people around you better
You stay curious and keep learning
You see a problem and start solving it, without waiting to be asked
You keep the whole pipeline in view and notice how a change in one place ripples through the data, the release, and the team
You document your work clearly enough that someone else can pick it up
You communicate well with data managers, stewards, and subject matter experts who don't share your technical background
You take data quality and responsible stewardship of research data seriously

About the Role

This is a hands-on data engineering role working with our Study Operations team. The mission is simple to state and hard to do: make study data clean, well-documented, and release-ready, and run quality control and large-scale data sharing across the studies and consortia we support.

You take the pipelines that internal and external subject matter experts build for imaging, biospecimens, wearables, EEG, and other multi-modal study data, and turn them into standardized, production-ready workflows. You configure the containers that package the scientific software those pipelines run on, execute them efficiently across high-performance and cloud computing environments, and move data across the distributed storage platforms our studies use. You work closely with data managers, data stewards, the workgroups behind each study, and the internal and external pipeline developers whose work you standardize and scale.

What You'll Do

Data Engineering

Take pipelines built by internal and external subject matter experts and standardize them into scalable, production-ready workflows
Optimize pipeline performance and scalability as data volumes and study complexity grow
Maintain and continuously improve pipelines once standardized
Monitor the state of study data and report progress toward upcoming releases
Coordinate with data managers and data stewards on release timelines and data quality

Process Automation & Technical Leadership

Investigate agentic AI-assisted approaches to pipeline and process management
Advise Scientific Data Operations teams on their data processing needs
Contribute engineering effort to data processing needs on other Lasso-supported studies

Data Quality

Work with subject matter experts and external study partners to resolve data errors and discrepancies

Qualifications

Required

Bachelor's degree in Computer Science, Data Science, Neuroscience, Bioinformatics, or a related field plus 4+ years of relevant experience, or a master's degree in one of these fields plus 2+ years of experience
High comfort level with Linux and the command line
Experience with containers: Docker, Kubernetes, Apptainer/Singularity, or similar
Experience with High Performance Computing (HPC)
Experience with cloud computing: AWS, Azure, OpenStack, or similar
Programming experience in Python, R, or shell scripting
Experience with data analysis, ETL, or reporting work
Experience with Git

Preferred

Experience with workflow-management tools such as Apache Airflow, Datalad, or SQL
Familiarity with object stores such as AWS S3 or Ceph
Experience working with academic or clinical research investigators across multi-site studies
Experience working with NIfTI and DICOM medical imaging data
Familiarity with neuroimaging analysis tools such as FreeSurfer, FSL, or Connectome Workbench
Familiarity with machine learning, deep learning, and annotation workflows

Apply About employer

More about this job

Responsibilities

Standardize and optimize pipelines for multimodal research data into scalable, production-ready workflows, and configure containers to run them across high-performance and cloud computing environments. Monitor data quality and release progress, coordinate with study teams and pipeline developers, and help resolve data discrepancies and improve process automation.

Requirements

Requires a bachelor's degree in a relevant field plus at least four years of relevant experience, or a master's degree plus at least two years. Candidates need experience with Linux, containers, HPC, cloud computing, Python, R or shell scripting, data analysis or ETL, and Git; workflow tools, object stores, and research data experience are preferred.

Skills

Linux
Command Line
Docker
Kubernetes
Apptainer
High-Performance Computing
Cloud Computing
Python
R
Shell Scripting
Data Analysis
ETL
Git
Workflow Management
Data Quality
Data Engineering

Benefits

Competitive Compensation
Benefits
Flexible Work Arrangement
Growth Opportunities

Visa sponsorship

Not detected in the job text

Keywords

Data Engineering
Research Data Management
Multimodal Data
Pipeline Standardization
Production Workflows
Linux
Docker
Kubernetes
Apptainer
High-Performance Computing
Cloud Computing
AWS
Azure
OpenStack
Python
R
Shell Scripting
ETL
Git
Apache Airflow
Datalad
SQL
AWS S3
Ceph
NIfTI
DICOM
FreeSurfer
FSL
Connectome Workbench
Data Quality

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