Skip to content
remoty.work
For employers
Menu

Data Engineer

HuzzleSouth Africa

Data Science Mid level Full Time

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.

Originally posted on Himalayas

Apply for this role Opens himalayas.app — the link as listed; we have not yet verified it is the employer's own page

Keep looking

Similar remote roles, still open

See every "Data Engineer" role →

Or follow the daily Telegram channel for the best new remote roles every morning.

Your turn · no account needed

Help the next applicant

You may know something about this listing that we cannot see from here. One tap. No account needed. Signed-in reports earn points once the evidence agrees with you.

I know what it pays

What you were offered, quoted in an interview, or paid in this role. A range is fine.

Sign in with Google to earn points for reports.

Where this listing came from

  1. 01 Oct 2026Himalayas first sighting

Seen on 1 board over 0 days.