Bilal Ijaz

Senior Data Engineer

Datamount • Período integral

Dec 2025 - Aug 2026 • 8 mos

• Engineered the Preferred Travel Group and Polaris I/O data platform using Microsoft Fabric and dbt, implementing Bronze, Silver, and Gold transformation workflows and improving downstream data consistency and processing reliability by 40%. • Designed and implemented an automated Amperity reservation pipeline to extract parameterized reservation data, apply business rules and validation checks, and securely deliver processed datasets through Azure Blob Storage and SFTP, reducing manual data-processing effort by 40%. • Implemented automated data-quality and reconciliation controls, including 0-byte file detection, SQL-to-Blob row-count validation, blob-size validation, and end-to-end delivery checks, improving data-quality assurance by 45% and reducing manual valida tion effort by 50%. • Automated daily reservation processing using parameterized start/end-date logic, scheduled triggers, monitoring, retry mechanisms, and operational logging, achieving 99%+ reliable data delivery to downstream Amperity workflows. • Developed and optimized SQL Server → Azure Blob → SFTP data movement pipelines with Azure Data Factory, reducing data delivery processing time by 30% and minimizing operational intervention by 40%. • Contributing to a risk-scoring data platform integrating structured data from SFTP, Microsoft Dynamics, Salesforce, NLP-generated articles, and government sources, designing standardized processing workflows that improve multi-source data preparation efficiency by 30%

Associate Cloud and Data Engineer

Codet AI • Período integral

Feb 2023 - Dec 2025 • 2 yrs 10 mos

• Designed and managed the complete multi-tenant data pipeline architecture in GCP, including Billing Pipelines and Tenant resource use pipelines, improving tenant resource tracking and billing automation efficiency by 50%. • Built centralized tenant usage monitoring systems using GCP Cloud Logging, Log Filters, BigQuery, Pub/Sub, and Cloud Run to process backend API and infrastructure usage data in real time with 99.9% pipeline availability. • Developed and automated CI/CD pipelines using Bitbucket and Google Cloud Build, reducing deployment failures by 40% and accelerating release cycles by 30%. • Implemented GA4 Analytics and Heatmap integrations to capture user behavior, click events, movement tracking, device-wise analytics, and section-wise engagement metrics, increasing reporting accuracy by 70%. • Designed scalable event-streaming pipelines to transform GA4 and application events into Big-Query Data Warehouses, enabling near real-time business intelligence and reducing the time of analysis queries by 40%. • Deployed and managed Yugabyte Distributed Database Clusters with automated backups,real-timemonitoring,andhigh-availability architecture, ensuring zero downtime and 100% recovery readiness.

Data Engineer

Bytewise Limited • Período integral

May 2022 - Jan 2023 • 8 mos

• Built and optimized ETL/ELT pipelines using Apache Spark and Databricks, reducing data processing time by 40%. • Automated multi-source data ingestion workflows, improving data availability and operational productivity. • Implemented data validation, transformation, and quality checks, reducing inconsistencies and missing values by 95%. • OptimizedAzure Data Lake storage and query workflows, improving analytics performance while reducing infrastructure costs. • Developed scalable real-time and batch data pipelines for data warehousing and analytics solutions using cloud-native technologies.