Professional Experience

Data Engineer — NatWest Bank

September 2025 – Present | Greater London, UK

Building and maintaining production data platforms that process millions of transactions daily, supporting analytics and regulatory reporting across the organization.

Key Responsibilities:

  • Design and implement real-time data ingestion pipelines using Kafka and Amazon S3
  • Develop distributed data processing workflows with PySpark for transformation and validation
  • Build curated data models in Snowflake supporting downstream analytics and reporting
  • Orchestrate end-to-end pipelines using Apache Airflow DAGs with dependency management and monitoring
  • Collaborate with cross-functional teams on data architecture, governance, and documentation
  • Optimize SQL and PySpark workloads for performance and cost-efficiency
  • Publish business-ready datasets and dashboards via Tableau

Technologies: Kafka, PySpark, Amazon S3, Snowflake, Apache Airflow, Python, SQL, Tableau, Jira, Confluence

Impact: Enabled reliable data flows supporting critical business operations, analytics, and regulatory compliance

Data Engineer — Accenture

July 2023 – August 2025

Delivered large-scale cloud data engineering solutions for enterprise clients across multiple industries, working with both Azure and AWS cloud platforms.

Key Responsibilities:

  • Designed and implemented scalable ETL/ELT pipelines using Azure Databricks, Azure Data Factory, and Snowflake
  • Developed PySpark workflows for distributed data processing and transformation
  • Built reusable transformation layers with dbt, ensuring consistent business logic and modular data models
  • Automated pipeline deployments using CI/CD (GitHub Actions, Terraform)
  • Implemented data quality checks, schema evolution strategies, and governance controls
  • Optimized query performance across Databricks, Snowflake, and cloud data lakes
  • Leveraged Microsoft Fabric for unified analytics workflows and lakehouse architecture
  • Produced technical documentation and data flow diagrams supporting cross-team collaboration

Technologies: Azure Databricks, Azure Data Factory, Azure Data Lake, Snowflake, PySpark, dbt, Microsoft Fabric, AWS (S3, Glue), Python, SQL, Terraform, GitHub Actions

Impact: Delivered data platforms enabling analytics, reporting, and machine learning for Fortune 500 clients

Data Engineer — Dpoint Group

May 2022 – June 2023 | Barcelona, Spain

Contributed to business intelligence and analytics initiatives, building ETL pipelines and reporting solutions that supported operational decision-making.

Key Responsibilities:

  • Developed and maintained ETL processes using SSIS to extract data from SAP BW
  • Created interactive Power BI dashboards for executive insights and KPI monitoring
  • Wrote optimized SQL queries, views, and stored procedures for reporting and analytics
  • Automated recurring reporting workflows using Python and Excel VBA
  • Supported migration of on-premise ETL processes to Azure Data Factory
  • Implemented version control and documentation standards for data pipelines

Technologies: SSIS, SAP BW, Power BI, Azure Data Factory, Python, SQL, Excel VBA, Git

Impact: Improved reporting efficiency and reduced manual workload through automation

Education

Master of Business Administration (MBA)
York St John University, London, United Kingdom
2023 – 2024

Bachelor of Internet & Communication Technology
Tor Vergata University, Rome, Italy
2020 – 2023

Certifications

Microsoft Certified: Fabric Data Engineer Associate

Microsoft | January 2026 – January 2027
Credential ID: 1D3467-780915
Verify Credential

Validated expertise in building and managing data engineering solutions on Microsoft Fabric, including:

  • Data lakehouse architecture with OneLake and Delta Lake
  • Building data pipelines with Data Factory and Dataflow Gen2
  • Real-time analytics with KQL databases and Eventstream
  • Data transformation with Notebooks and Spark
  • Power BI integration and semantic modeling
  • Data governance and security in Fabric workspaces

Additional Training & Certifications

In Progress:

  • AWS Certified Solutions Architect
  • Azure Data Engineer Associate

Completed:

  • Apache Airflow workflow orchestration
  • Databricks Apache Spark certification training

  • dbt Analytics Engineering fundamentals

Skills Summary

Programming: Python (PySpark, Pandas), SQL, Shell Scripting
Cloud Platforms: AWS, Azure, Microsoft Fabric
Data Engineering: Apache Kafka, Apache Airflow, Snowflake, dbt, ETL/ELT
Databases: Snowflake, Azure SQL, Redshift, PostgreSQL, MySQL
DevOps: Docker, Terraform, CI/CD, Git, GitHub Actions
BI Tools: Tableau, Power BI
Methodologies: Agile/Scrum, Data Modeling, Data Architecture

← Back to Home View Open Source Contributions →