Data Engineer

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FROSTBYTE

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Job Summary


Job Type
-

Seniority

Years of Experience
Information not provided

Tech Stacks
Python SQL Azure Databricks pySpark CI Azure Data Lake Factory ETL

Job Description

Overview

We are hiring a Mid–Senior Data Engineer with strong expertise in Azure cloud, Databricks, PySpark, and orchestration of data pipelines. The ideal candidate must hold a minimum of an Honours degree in an IT-related field and be experienced in building scalable, automated data solutions on Azure.


Key Responsibilities

  • Design, develop, and maintain scalable and automated data pipelines using Azure Data Factory, Azure Databricks, and Azure Data Lake.
  • Build and optimize PySpark-based data workflows in Azure Databricks for batch and streaming workloads.
  • Develop ETL/ELT processes and ensure reliable orchestration and scheduling of data workflows.
  • Implement CI/CD practices and DevOps methodologies for data pipeline deployments.
  • Ensure high availability, performance, and security of data pipelines in production environments.
  • Monitor, troubleshoot, and resolve issues in data workflows and pipeline performance.
  • Document data pipelines, architectures, processes, and operational procedures.
  • Collaborate with architects and engineering teams to design efficient and scalable data solutions.
  • Mentor junior data engineers and contribute to best practice adoption.


Minimum Qualifications

  • Honours Degree in Computer Science, Information Technology, Computer Engineering, or a related field (minimum NQF Level 8).


Experience Required

  • 5+ years' experience in data engineering within a cloud-based environment.
  • Hands-on experience with Azure Databricks, PySpark, Azure Data Factory, and Azure Data Lake.
  • Experience in designing and orchestrating end-to-end data pipelines.
  • Experience working with CI/CD, DevOps practices, and version control for data engineering workflows.


Core Technical Skills

  • Advanced SQL and strong Python programming with a focus on PySpark.
  • Azure Databricks for building, transforming, and optimizing data workflows.
  • Azure Data Factory for pipeline orchestration, scheduling, and monitoring.
  • Experience with Azure Data Lake (Gen2) for data storage and management.
  • Designing, deploying, and managing ETL/ELT pipelines.
  • Troubleshooting, performance tuning, and monitoring data pipelines.
  • Ability to write clear technical documentation and architectural diagrams.


Soft Skills

  • Strong analytical and problem-solving ability.
  • Excellent communication and interpersonal skills.
  • Ability to work in cross-functional teams and mentor junior engineers.


Please note: The work type for this position is 5 days in office.


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