freehire launches on Product Hunt on 26 August.

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Intermediate Data Engineer

Summary

Build and maintain scalable data pipelines using Databricks, Apache Spark, and Azure, automating workflows and CI/CD to deliver reliable, high-performance data solutions.

Key Responsibilities

Data Engineering & Platform Development

  • Design, build, and maintain scalable data pipelines and workflows.
  • Develop and optimise data processing solutions using Databricks and Apache Spark.
  • Build and support end-to-end data integration and transformation processes.
  • Ensure data solutions are reliable, efficient, and aligned with best-practice engineering standards.

Cloud & Big Data Solutions

  • Develop solutions within Azure cloud environments.
  • Support the implementation and optimisation of modern data architectures.
  • Work with large-scale datasets and distributed computing frameworks.
  • Contribute to the ongoing evolution of the organisation's data platform capabilities.

Data Pipeline Automation & CI/CD

  • Develop and maintain CI/CD pipelines to support efficient deployment and release processes.
  • Implement automation strategies that improve data delivery, quality, and operational efficiency.
  • Support monitoring, testing, and optimisation of data engineering workflows.

Collaboration & Solution Delivery

  • Work closely with Data Engineers, Developers, Analysts, and Business Stakeholders to deliver high-quality data solutions.
  • Participate in solution design discussions and technical planning.
  • Contribute to the continuous improvement of data engineering practices and standards.

Innovation & Continuous Learning

  • Stay current with emerging technologies and trends within data engineering and cloud platforms.
  • Identify opportunities to improve performance, scalability, and maintainability across data solutions.
  • Contribute to knowledge sharing and technical excellence within the team.

Requirements

Essential Skills & Experience

  • 3-5 years' experience in a Data Engineering, Backend Development, or similar technical role.
  • Previous experience working as a Data Engineer.
  • Strong experience with Databricks.
  • Proven expertise in Apache Spark and cluster computing environments.
  • Advanced Python skills, including mandatory PySpark experience.
  • Strong SQL development skills.
  • Experience developing and maintaining CI/CD pipelines.
  • Experience building scalable and reusable data pipelines.
  • Solid software engineering and backend development foundations.
  • Exposure to Azure cloud services and infrastructure.

Advantageous Experience

  • Microsoft Fabric experience.
  • Medallion Architecture experience.
  • Experience working with modern data warehousing and analytics environments.
  • Exposure to cloud-native data engineering practices.

What Success Looks Like

  • High-performing and scalable data pipelines are delivered and maintained.
  • Data workflows are optimised for reliability, performance, and cost efficiency.
  • CI/CD processes support efficient and consistent deployments.
  • Strong collaboration with technical and business teams results in high-quality data solutions.
  • Best practices for data engineering, cloud development, and automation are continuously adopted and improved.


Apply now!

See also