Iryna Vanahel

Cloud and Data Engineering Professional with 10+ years of experience designing enterprise data solutions, cloud integrations, and scalable technology architectures across GCP, AWS, and Microsoft Azure. Experienced in cloud migration strategy, solution design, secure cross-cloud integration, data architecture, and production reliability. Proven ability to translate business and technical requirements into scalable architecture solutions, define technical requirements, and collaborate with infrastructure, DevOps, and business teams to deliver secure, maintainable, and high-performance cloud environments.

Data Engineer - GEOTAB - Canada

(2020-11)

• Designed and maintained enterprise cloud data architecture supporting 20+ production Apache Airflow DAGs using GCP Cloud Composer, Python, and SQL, integrating Salesforce, Jira, Dynamics 365 F&O, AWS S3, Microsoft Fabric, and other enterprise platforms.
• Architected a secure AWS-to-GCP cloud migration framework using Amazon S3, Google Cloud Storage, Storage Transfer Service, Python, SQL, Airflow, and BigQuery. Defined manifest-driven migration patterns, primary and backup transfer paths, status validation, checksum verification, audit logging, and automated stakeholder reporting.
• Designed cross-cloud integration and access requirements for secure data transfers between AWS and GCP, including regional landing zones, confidential storage locations, read-only cross-cloud IAM access, and controlled transfer workflows without long-term credentials.
• Defined scalable cloud storage and warehouse architecture using GCS and BigQuery, incorporating partitioning, clustering, schema versioning, CSV and Parquet processing, data reconciliation, and multi-region deployment requirements.
• Architected and optimized a large-scale Dynamics 365 Finance & Operations integration using Microsoft Fabric, GCS, Apache Airflow, Python, SQL, and BigQuery. Implemented automated table discovery, parallelized incremental Parquet exports, idempotent processing, and historical change tracking, reducing refresh time for a 700M+ row table from 80 minutes to under 4 minutes.
• Designed enterprise integration patterns using Python, REST APIs, SQL, and Apache Airflow, replacing full-table reloads with incremental ingestion and consolidating six legacy Jira tables into a streamlined BigQuery data model.
• Led data architecture and relational schema design for an internal application replacing a third-party platform, translating business requirements into maintainable data structures and integration workflows.
• Established architecture and operational controls for production pipelines, including data validation, checksum verification, duplicate detection, audit logging, monitoring, schema management, and failure-handling processes.
• Collaborated with CloudOps and DevOps teams to define infrastructure, access, security, and deployment requirements; provided technical specifications and coordinated implementation through the appropriate engineering teams.
• Produced technical documentation covering cloud integrations, data flows, schemas, migration processes, operational procedures, and data validation requirements.

Data Analytics - SMARTCENTRES REIT - Toronto, Canada

(2018-02 - 2020-11)

• Designed and developed Python-based ETL workflows to cleanse, enrich, validate, and standardize data from multiple enterprise sources.
• Built SQL Server extraction and transformation processes, delivering analytics-ready datasets with embedded data quality controls.
• Developed Tableau dashboards and analytical datasets supporting forecasting, scenario modeling, property valuation, and business performance analysis.
• Developed a Python/Pandas analytical model that reduced analysis time by 60%.
• Worked with business stakeholders to translate reporting requirements into data solutions, standardize metrics, and improve data consistency.

Analyst - HARMONIC FUND SERVICES - Toronto, Canada

(2016-12 - 2018-02)

• Automated financial reconciliation and variance-analysis processes using Python, SQL, and Excel, reducing processing time by approximately two-thirds.
• Developed SQL-based data validation and reconciliation controls to improve the accuracy and completeness of fixed-income portfolio data.
• Built financial data models and reporting workflows consolidating multiple internal and external sources.
• Collaborated with stakeholders to identify process improvements and coordinate technical changes through Jira.

Analyst - JONES LANG LASALLE - Toronto, Canada

(2013-10 - 2016-12)

• Automated transaction, leasing, and revenue reporting workflows using Python, VBA, SQL, and Excel, improving processing efficiency by approximately 50%.
• Developed SQL-based data aggregation, KPI reporting, and financial models to support business decisions.
• Built discounted cash flow (DCF), net present value (NPV), and sensitivity analysis models.
• Documented business rules, reporting logic, and analytical requirements to improve process consistency.

Analyst - BELARUSBANK

(2005-07 - 2008-02)

• Supported treasury product analysis, financial reporting, and data-driven business processes within a banking environment.

Diploma - Applied Data Engineering & Architecture - Toronto Institute of Data Science and Technology

Course - Data Organization for Data Analysts - Ryerson University

Bachelor’s Degree - Economics - Belarusian State Economic University