Data Engineering Manager | 15 years Experience | Azure, Python, SQL, ETL, CI/CD

I am results-driven and innovative Data Engineering Leader with over 15 years of proven expertise in architecting, leading, and scaling enterprise-grade data platforms. With a deep command of Microsoft Azure and modern data ecosystems, I have consistently delivered impactful solutions that drive business transformation, strategic decision-making, and operational efficiency across the financial services, fintech, gaming, and public sectors. Currently serving as Associate Director and Data Engineering Manager at Pemberton Asset Management, I lead a high-performing team of data engineers focused on building secure, scalable, and automated data infrastructure. My leadership blends deep technical acumen with a sharp business sense, enabling me to align data strategy with broader organizational objectives. Throughout my career, I have been recognized not only for my hands-on capabilities with cloud platforms, ETL/ELT pipelines, and automation tools, but also for my ability to mentor, inspire, and empower teams to deliver consistently high-quality outcomes.

Core Philosophy: Data-Driven Business Growth

I am deeply passionate about the transformative power of data. I see data engineering not as a support function, but as a strategic enabler for innovation, efficiency, and value creation. Whether it’s modernizing legacy infrastructure, enforcing governance, or facilitating cross-functional data collaboration, my goal is simple: to turn data into a competitive advantage.

Leadership and Strategy

My leadership is characterized by a hands-on, collaborative approach. At Pemberton, I oversee the full lifecycle of data projects—from architectural design through delivery and maintenance—ensuring alignment with the needs of finance, risk, and operational stakeholders. Under my leadership, the data engineering team has delivered key innovations, including:

• The migration of the data estate to Azure, resulting in a 40% reduction in data processing times and enhanced data accessibility across the business.
• Development of an automated investor reporting platform, reducing report generation times by 95% and eliminating all human error.
• Implementation of CI/CD pipelines via Azure DevOps, dramatically improving deployment efficiency and reducing time-to-value by 30%.

I am also a firm believer in cultivating a learning culture. I actively mentor junior engineers, boosting team capability by over 25% in my current role, and I promote best practices in code quality, testing, and cloud-native development.

Technical Mastery Across Cloud and Data Stacks

I am expert in Microsoft Azure, including core services such as Azure Data Factory (ADF), Synapse Analytics, Azure Data Lake Storage (ADLS), Databricks, Azure SQL, and Microsoft Fabric. I am also well-versed in AWS Redshift, Power BI, Tableau, and various orchestration and automation tools such as Apache Airflow, Azkaban, and Azure Logic/Function Apps. I have extensive experience designing and deploying data pipelines and architectures tailored to meet the growing needs of analytics teams and business users. My strengths in SQL, Python, PySpark, and ETL/ELT methodologies are matched by my commitment to data governance, compliance, and quality control. In addition to my engineering expertise, I am an advocate of robust DevOps practices. Using tools such as Azure DevOps and Git, I ensure that my team delivers code that is secure, version-controlled, and continuously integrated/deployed across environments.