01Overview
Key Responsibilities
Design, develop, and maintain scalable data pipelines and data integration processes.
Build and optimise databases for performance, reliability, security, and scalability.
Develop efficient SQL queries, stored procedures, and database objects for data processing and reporting.
Design and implement data models and database schemas to support business applications and analytics.
Manage and maintain PostgreSQL and MongoDB databases, ensuring high availability, backup, recovery, and performance tuning.
Work with application developers to integrate databases with enterprise applications.
Collaborate with business analysts to build dashboards, reports, and visualisations.
Work with structured and unstructured data from multiple data sources.
Monitor database health, troubleshoot issues, and implement performance improvements.
Evaluate and implement modern data engineering tools and technologies.
Maintain technical documentation for databases, data pipelines, and ETL/ELT processes.
Qualifications & Experience
The ideal candidate should have:
25 years of experience as a Data Engineer, Database Engineer, or a similar role.
Strong knowledge of SQL and relational databases such as PostgreSQL or MySQL.
Experience writing complex SQL queries for reporting and analytics.
Hands-on experience with MongoDB, including schema design, indexing, aggregation pipelines, and query optimisation.
Experience in database administration, performance tuning, backup, and recovery will be an added advantage.
Strong understanding of data modelling and database design principles.
Familiarity with Business Intelligence (BI) tools such as Power BI, Tableau, or Apache Superset.
Familiarity with Apache Airflow and Airbyte will be an added advantage.
Good understanding of data quality, security, and data governance best practices. .
