Description review

Data Engineer

Huzzle · South Africa · back to the listing

HR standards

61/100

needs work

Title ↔ description

91/100

strong

Reads as

Data Engineer

100% confident

How others title the same work

Large employers

  • Data Engineer, Product Analytics Meta
  • Senior Staff Data Engineer Mozilla
  • Staff, Analytics Engineer, GTM Data Science & Analytics Twilio
  • Senior Software Engineer - Data Platform Coinbase
  • Senior Security Data Engineer Doordash

Startups

  • Business Intelligence Engineer GoSats
  • IPinfo.io | Data Engineer | REMOTE (Anywhere) | Full-time IPinfo.io
  • Senior Data Engineer Camber
  • Senior Data Engineer Instrumentl
  • Cardog | Toronto, Canada or REMOTE | Full-time Cardog

What the listing never says

  • 21 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
  • No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency

The listing, marked up

Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.

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

How this was produced

Highlights are found by rule, not by a model: each one is a phrase matched at a known position, and every note is a template we wrote. The two scores come from a typed-decision model (Jev) that reads the listing against the official role definition and real listings for the same role, and returns probabilities rather than prose — it never writes any of the words on this page, and never chooses what to highlight.

Deterministic penalty applied to the HR score: 8 points (from 69 before penalties). Reviewed 1 Oct 2026.