BI Data Engineer (Remote)

Datafin; Cape Town; Remote; ZAR 45 000 - 75 000; Full time

Job summary

An innovative Travel Tech company in Cape Town is on the lookout for a talented BI Data Engineer to enhance its data infrastructure and transform raw data into impactful insights. In this dynamic role, you will manage the entire data pipeline, collaborating closely with product teams to streamline processes and improve data quality. Your expertise in predictive analytics and data modeling will be crucial in driving strategic decisions that elevate business outcomes. Join a forward-thinking team dedicated to leveraging data for meaningful impact, and help shape the future of travel technology.

Qualifications

• 5+ years of experience in BI, data engineering, or a similar role.
• Strong skills in data modeling and predictive analytics.

Responsibilities

• Manage and optimize BI/Data infrastructure costs through GCP.
• Lead the end-to-end data pipeline process from ingestion to reporting.

Skills

Data Engineering

Predictive Analytics

Data Modeling

Machine Learning

Google Cloud Platform (GCP)

PowerBI

Google Analytics

Google Tag Manager

Education

Relevant Degree

Tools

PowerBI

Google Analytics

Google Tag Manager

Job description

ENVIRONMENT:

A leading Travel Tech company in Cape Town is seeking a BI Data Engineer to optimize its data infrastructure and turn raw data into actionable insights that drive strategic decisions. You will manage the full data pipeline—from ingestion and transformation to reporting and visualization—while leveraging your skills in predictive analytics and data modeling to enhance business outcomes. Working closely with Product squads and Account Managers, you’ll bridge gaps in processes and systems to strengthen the data ecosystem. A relevant degree and 5+ years of experience in BI, data engineering, or a similar role are required.

DUTIES:

1. Manage, monitor, and optimize BI / Data infrastructure costs through GCP.
2. Lead and improve the end-to-end data pipeline process, from data ingestion and transformation to reporting systems, automating as much as possible.
3. Introduce AI tools and methodologies across the data pipeline to improve efficiencies, data monitoring, data quality and overall business value delivered.
4. Collaborate with peers and stakeholders to understand and translate business requirements into robust data solutions.
5. Design, develop, and maintain data models, including machine learning models, ensuring data accuracy, reliability, availability, and evolution.
6. Use reporting tools such as PowerBI to create and automate comprehensive data visualizations and reports.
7. Manage Google Analytics and Google Tag Manager accounts to drive decisions for web-based platforms.
8. Communicate actionable insights with proactive recommendations using statistical techniques.
9. Collaborate with stakeholders to identify new opportunities for data insights and develop strategies to meet business goals and drive more value to their clients.
10. Create and maintain reporting templates and dashboards for internal and external audiences.
11. Independently identify, troubleshoot, and resolve data-related issues, ensuring a seamless data flow and maintaining high data quality and accuracy standards.
12. Take ownership of data-related decisions and provide guidance on future data-specific hiring needs as well as tools.