Assistant Manager, Data Quality & Analytics

Socket.dev; Montreal (administrative region); Hybrid; CAD 70,000 - 110,000; Full time

Benefits offered by this job

Remote work

Hybrid work

Work from abroad policy

Birthday off

Job summary

IATA in Montreal seeks an Assistant Manager – Data Quality & Analytics to support the Turbulence Aware NextGen platform migration, contribute to data quality governance, testing coordination, business analysis, and data science activities. The role applies statistical profiling, anomaly detection, and Python-based analysis to monitor data quality and ensure accuracy and traceability across the platform.

You will document data dictionaries, validation rules, business rules, and dashboards,

Qualifications

• 3–5 years’ experience in data analytics or data science.
• Experience with data validation, anomaly detection, and data quality.
• Familiarity with aviation or complex operational data domains is a plus.

Responsibilities

• Support Data Quality Governance, Assurance & Control.
• Assist in data migration preparation and reconciliation.
• Apply statistical profiling, trend analysis, and data validation techniques.

Tools

SQL

Python

Data Analysis

Data Profiling

Anomaly Detection

Power BI

Tableau

Looker

Job description

Employment Type: Permanent

Contract Duration:

Why you will love working here

At IATA, we represent over 350 airlines worldwide, striving to make aviation safer, smarter, more sustainable, and inclusive.

• Our Values are not just words on a page - they are the energy behind everything we do: ONE IATA- We collaborate across teams,TRUSTED-We do the right thing,INNOVATIVE-We make tomorrow better,INCLUSIVE-We embrace diverse perspectives.
• With over 30,000 courses available, we believe in continuous learning and support your growth in an ever-changing industry.
• Diversity, equity, and inclusion are our priorities. We are certified by the Equal Salary Foundation, offering equal pay and family-friendly policies.
• We encourage community involvement through volunteering and strive to make tomorrow better for aviation and our communities. We offer time off so you can support causes important to you.
• We promote work-life balance with flexible work options, including remote and hybrid work, a generous 'work from abroad' policy, and you get your birthday off!

About the team you are joining

The Assistant Manager – Data Quality & Analytics will support the Turbulence Aware NextGen platform migration by contributing to data quality governance and control, migration readiness, acceptance testing coordination, business analysis, and data science activities.

What your day would be like

Therole will support the Assistant Director, Turbulence Aware NextGen, indesigning and validating the Data Quality Control Module of TA NextGen. Therole will also help ensure that migration activities, comprehensive testing,data quality assurance, and new analytics features are delivered with accuracy,reliability, and full requirements traceability.

Therole will apply analytical and data science techniques, including statisticalprofiling, anomaly detection, data validation, and Python-based analysis, tosupport the monitoring and continuous improvement of data quality across theplatform.

Key Responsibilities

1. Data Quality Governance, Assurance & Control

• Support the definition and documentation of data quality requirements, including applicable standards, validation rules, business rules, thresholds, and acceptance criteria, to help ensure the reliable and continuous operation of the Turbulence Aware NextGen platform.
• Support the Assistant Director in designing and validating the Data Quality Control Module of TA NextGen.
• Support the design of the Quality Control Module, including quality KPIs, dashboards, alerts, and data science-based controls for:
• Airline-provided EDR and ACARS data
• Third-party supplemental data
• Output datasets distributed to airline participants
• Support issue resolution with airlines, developers, infrastructure teams, vendors, and internal stakeholders.

2. Data Science Support for Data Quality Control

• Support the use of data science techniques to improve data quality assurance and control across the TA NextGen platform.
• Analyze historical and near-real-time datasets to identify patterns, gaps, inconsistencies, latency issues, and abnormal reporting behavior.
• Apply statistical profiling, trend analysis, anomaly detection, and data validation techniques to identify data quality issues and monitor data reliability with automated or semi-automated data quality checks using SQL, Python, or similar tools.
• Prepare analysis outputs, notebooks, reports, or dashboards to explain data quality findings to technical and non-technical stakeholders.

3. Data Migration Preparation & Reconciliation

• Support pre-migration data profiling and baseline validation activities.
• Assist in developing reconciliation frameworks for legacy vs. new platform outputs.
• Use SQL, Python, or analytical tools to compare datasets, identify discrepancies, and support reconciliation evidence.
• Track and document discrepancies, resolution actions, and sign-off criteria.
• Support cutover readiness assessments and post-migration stabilization reviews.

4. Support for Turbulence Aware Platform Migration andNew Feature Delivery

• Support the development and validation of new revenue-generating features.
• Assist in defining acceptance criteria and validation metrics for nowcast, forecast, and warning products.
• Support testing activities by preparing, documenting, and maintaining test scripts, and help track test execution progress.
• Help verify that deployed features meet defined quality, latency, and reliability standards.
• Assist in preparing documentation and dashboards for customers' onboarding and commercialization.

5. Documentation & Governance

Maintain comprehensive documentation, including:

• Data dictionaries
• Validation rules
• Business rules
• Data science assumptions and analytical methods
• Test plans and scripts
• Reconciliation reports
• Analytics feature specifications
• Data quality dashboards and KPI definitions

We would love to hear from you if

3–5 years’ experience in one or more of the following areas:

• Data science or applied analytics
• Data validation and anomaly detection
• Data platform migration
• Business analysis in analytics-driven environments
• Strong analytical background with the ability to assess structured datasets, identify patterns, investigate anomalies, and interpret data quality KPIs.
• Working knowledge of SQL and Python for data analysis, data profiling, validation, reconciliation, and basic automation.
• Familiarity with data science techniques such as statistical analysis, outlier detection, trend analysis, anomaly detection, and data visualization.
• Demonstrated basic knowledge of aviation operations and associated data domains, or strong interest and ability to quickly learn complex operational data domains.
• Familiarity with streaming data, cloud-based architectures, data pipelines, or near-real-time analytics is an asset.
• Familiarity with BI and visualization tools such as Power BI, Tableau, Looker, or similar platforms is an asset.

Travel Required: N