- Data pipelines migration from Teradata to Databricks- Optimisation of existing pipelines- Tools development- Incidents recovery and investigation

- Design and develop scalable and reliable data pipelines for calculating key product metrics on a daily and monthly basis, leveraging technologies such as HDFS, Hive, and Spark.- Automate manual product pipelines and increase the frequency of data updates from 2 times a week to daily, resulting in improved data accuracy and reduced time-to-insight.- Develop and maintain dashboards for data visualization, enabling business stakeholders to easily monitor the health of the product and identify issues quickly.- Collaborate with cross-functional teams, including data scientists, analysts, and product managers, to understand business requirements and translate them into technical solutions.- Conduct ad-hoc data analysis and reporting to support business decision-making, using tools such as Python and SQL.- Continuously identify opportunities to improve data quality, reliability, and accessibility, and drive the implementation of data engineering best practices across the organization.

- Conducted data analysis and produced reports to support decision-making.- Collaborated with cross-functional teams to design and implement new initiatives and programs.- Utilized Python and SQL for data analysis and automation, saving hundreds of work hours on multiple projects.