Manuel Meireles
I'm Manuel Meireles, a Senior Cloud Data Engineer with 10+ years of building scalable data platforms, streaming pipelines, and analytics architectures across GCP, Azure, and AWS.
About
I’m Manuel Meireles, a Senior Cloud Data Engineer with 10+ years of building scalable data platforms, streaming pipelines, and analytics architectures across GCP, Azure, and AWS. I design and operate enterprise data warehouses and lakehouses, delivering reliable, scalable analytics for complex business domains.
I’ve led multi-cloud data initiatives for fast-growing eCommerce and SaaS environments, building real-time streaming, data governance, and ML-ready data platforms. My work emphasizes measurable business impact, from accelerating reporting and reconciliation to modernising logistics ETL and enabling AI-powered data lineage and governance.
- 7 years' experience
- Joined November 2025
Industry experience
- Retail
- Software & Internet
- Financial Services
- Transportation & Logistics
Work experience· 4 roles
Designed a configuration-based ETL framework for Microsoft Navision, supporting retail data integration into EDW. Migrated 3TB of on-prem SQL Server workloads to Azure SQL Data Warehouse with zero data loss. Built ADF pipelines (Linked Services, Datasets, Azure SQL, Blob, Data Warehouse) to automate ingestion and transformations. Developed Spark SQL, T-SQL, and SSIS pipelines for business-critical retail, finance, and operations analytics workloads.
Designed and operated a 10TB+ enterprise data warehouse and cloud data lake supporting analytics across checkout, payments, finance, and CRM. Built multi-cloud ingestion using Pub/Sub, Dataflow, BigQuery, and Apache Beam; delivered a high-throughput Kafka and Google Dataflow streaming pipeline processing 100k events/sec, reducing reporting latency to under 10 minutes. Led Finance Transformation by developing a dbt- and BigQuery-based Finance Data Mart enabling real-time reconciliation with partners and supporting key financial processes. Implemented CI/CD for data pipelines using Airflow, Python, Terraform; reduced deployment time and standardized environments. Automated finance reconciliation using Python Cloud Run functions, recovering $2M in previously untracked transactions. Modernised logistics ETL from batch to streaming (Kafka + Beam), reducing processing time from 24 hours to 30 minutes and handling 500k+ packages/month with 60M events. Built Terraform-driven CI/CD with Azure P
Designed enterprise Data Warehouse and SSAS tabular models to support global e-commerce analytics. Built clickstream analytics solutions enabling user behaviour insights and high-volume traffic monitoring. Implemented near-real-time sales monitoring pipelines using SQL Server Change Tracking (5-minute refresh). Optimised performance of large-scale analytical models and MDX queries to meet global SLA requirements.
Education
Hire Manuel Meireles today
Post a job and invite Manuel, or contact them directly. No hidden commission.