Data Engineer
Huzzle Open · verified Oct 24, 2026 At a glance
Mid-level Data Engineering role at Huzzle. Remote, South Africa · full-time.
Pay not stated Data Engineer salary
dataroles summary, based on the employer's posting.
What you'll do
- Build and maintain ETL and ELT pipelines that move data reliably
- Shape data architectures, databases and warehouses, improving storage and query performance
- Connect data from varied sources, including APIs and third-party platforms
- Check data quality and security, and troubleshoot pipeline issues
- Document data models and workflows while supporting reporting and analytics needs
What you bring
- At least three years in data engineering, data warehousing or a related role
- Strong SQL skills and experience managing databases
- Practical work developing data pipelines with ETL or ELT tools
- Programming experience in Python, Java, Scala or a comparable language
Who this fits
This role suits a mid-level data engineer comfortable working independently and collaborating remotely with analysts, engineers and business stakeholders. It is a full-time remote role based in South Africa.
From the employer
About Huzzle
At Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms in industries such as SaaS, MarTech, FinTech, and AI.
Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team.
Job Type: Full-time
Location: Remote
Job Summary
As a Data Engineer, you will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure. You will work closely with data analysts, data scientists, software engineers, and business stakeholders to ensure reliable, accessible, and high-quality data across the organization.
This is an excellent opportunity for professionals who enjoy solving complex data challenges and building systems that support business intelligence, analytics, and machine learning initiatives.
Key Responsibilities
- Design, develop, and maintain scalable ETL and ELT pipelines.
- Build and optimize data architectures, databases, and data warehouses.
- Integrate data from multiple sources, APIs, and third-party platforms.
- Ensure data quality, consistency, reliability, and security.
- Monitor and troubleshoot data pipelines and workflows.
- Collaborate with analytics, engineering, and business teams to understand data requirements.
- Implement data governance and best practices for data management.
- Optimize data storage, processing performance, and query efficiency.
- Support reporting, business intelligence, and analytics initiatives.
- Document data models, workflows, and technical processes.
Requirements
- 3+ years of experience in data engineering, data warehousing, or related roles.
- Strong proficiency in SQL and database management.
- Experience with Python, Java, Scala, or similar programming languages.
- Hands-on experience with ETL/ELT tools and data pipeline development.
- Knowledge of cloud platforms such as AWS, Azure, or Google Cloud Platform.
- Experience with modern data warehouses such as Snowflake, Redshift, BigQuery, or Databricks.
- Familiarity with orchestration tools such as Airflow or Prefect.
- Understanding of data modeling, data governance, and data quality principles.
- Experience working with large datasets and distributed systems is preferred.
- Strong analytical, problem-solving, and communication skills.
- Ability to work independently in a remote, collaborative environment.
Benefits
💰 Competitive salary: Based on experience, technical expertise, and location.
🌎 Fully remote role: Work from anywhere with flexible working arrangements.
🚀 Career growth opportunities: Join innovative companies and work on impactful projects.
📈 Long-term opportunities: Build your career with growing global organizations.
🧠 Continuous learning: Exposure to modern data technologies, cloud platforms, and large-scale data systems.
🤝 Collaborative culture: Work alongside talented engineers, analysts, and business leaders.
⚙️ Cutting-edge technology: Gain experience with modern data stacks and cloud-native solutions.
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