Lead the development and optimization of data pipelines, ensuring efficiency and scalability.
Design, implement, and maintain data warehouses and ETL processes for seamless data integration.
Collaborate with cross-functional teams to understand data requirements and provide effective solutions.
Leverage tools like Data bricks to create, manage, and deploy data workflows.Ensure the quality, reliability, and performance of data systems and processes.
Mentor and guide junior data engineers, fostering growth and knowledge sharing within the team.
Manage and optimize SQL-based databases to support operational needs and reporting.
Provide leadership and technical expertise in data engineering practices.
Communicate effectively with stakeholders to understand business requirements and provide technical solutions.
Requirements
Strong expertise in SQL and Python , with the ability to write optimised queries and efficient code.
Hands-on experience with Data bricks and modern data processing frameworks.
In-depth knowledge of Data Warehousing , ETL processes , and cloud data solutions.
Excellent problem-solving abilities and a solution-oriented approach to data challenges.
Strong leadership skills, with experience leading and mentoring teams.
Exceptional communication skills, both verbal and written, to effectively collaborate with technical and non-technical stakeholders.
Experience with relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases is a plus.
Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and distributed computing technologies is desirable.
Experience in data visualisation tools (e.g., Tableau, Power BI).