Assistant Manager, Data Quality & Analytics

Employment Type:

Permanent
Contract Duration:

• Our Values are not just words on a page - they are the energy behind everything we do:
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• 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!

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

Therole will support the Assistant Director, Turbulence Aware Next Gen, in designing and validating the Data Quality Control Module of TA Next Gen. 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 the platform.

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 Next Gen platform. Support the Assistant Director in designing and validating the Data Quality Control Module of TANextGen. Support the design ofthe Quality Control Module, including quality KPIs, dashboards, alerts,and data science-based controls for:
Airline-provided EDR and ACARS data
- Third-partysupplemental data
- Output datasetsdistributed to airline participants Support issue resolution with airlines, developers, infrastructure teams, vendors, and internal stakeholders.

Support the use ofdata science techniques to improve data quality assurance and controlacross the TA Next Gen platform. Analyze historical and near-real-time datasets to identify patterns, gaps, inconsistencies,latency issues, and abnormal reporting behavior. Apply statisticalprofiling, trend analysis, anomaly detection, and data validationtechniques to identify data quality issues and monitor data reliability with automated or semi-automated data quality checks using SQL, Python, orsimilar tools.

Prepare analysisoutputs, notebooks, reports, or dashboards to explain data quality findings to technical and non-technical stakeholders.

Support pre-migrationdata 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 documentdiscrepancies, resolution actions, and sign-off criteria. Support cutoverreadiness…