Responsibilities & achievements

- Developed the backend infrastructure for a video conference application utilising the Twilio API, seamlessly integrated with Microsoft Booking for efficient appointment scheduling. - Architected the backend of a payment system using the iOS In-App Purchases SDK, Azure Functions, and Python for robust and efficient transaction processing. - Implemented an efficient queue system using Redis Queue, significantly reducing request waiting times and enabling effective parallel processing. - Designed and implemented the backend system for a data ingestion platform utilising Flask, containerised with Docker, and integrating Airbyte, Dagster, dbt, and Snowflake to replace an outdated legacy system. - Created scalable ELT pipelines on Azure using Databricks, Apache Spark, and Python for efficient data integration from varied sources, enhancing organisational decision-making

Responsibilities & achievements

- Migrated data to a newly developed data warehouse from Firebase and QuickBooks API, adhering to business rules for data warehousing and modeling in an Azure SQL Data Warehouse. - Designed and implemented robust data pipelines using Python, streamlining the organisation's data flow and integration processes. - Implemented data pipeline orchestration using Apache Airflow, which ensured efficient maintenance, updates, and overall management of the company's data warehouse.

Responsibilities & achievements

- Constructed and optimized data pipelines for seamless integration with Tableau, enabling efficient generation of reports and dashboards for in-depth data analysis and decision-making. - Defined, extracted, and processed KPIs from diverse data sources, ensuring accurate metrics to evaluate the company's strategic objectives' alignment and performance.

Responsibilities & achievements

- Developed robust BI solutions, providing client management with essential data insights to refine decision making and optimize commercial campaigns. - Crafted and optimized SQL queries and ETL packages using T-SQL and SSIS, ensuring seamless data ingestion from various source systems into the SQL Server data warehouse. - Created dynamic reports using PowerBI and SSRS, converting raw data into actionable insights that empowered strategic and operational decision-making processes. - Designed and developed multidimensional cubes using SSAS, facilitating efficient data retrieval and enhancing analytical capabilities for deeper insights. - Unified two legacy systems into a pre-existing data warehouse, employing best data modeling practices, and thoroughly documented the integration process. - Led data engineering efforts in response to the product team’s initiatives to profile customers and optimize marketing targeting campaigns.