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Data Engineer

Summary

Build and deploy cloud-native data platforms using Python, Spark, Kafka, and AWS, focusing on batch and streaming pipelines with modern DevOps practices.

This role is for a Modern Data Engineer with strong software engineering skills who can build and deploy cloud-native data platforms.

Key Requirements

Software Engineering

  • Strong Python development skills (primary programming language)
  • Solid understanding of software engineering principles and clean coding practices
  • Experience working within the Software Development Life Cycle (SDLC)
  • Proficient with Git and version control
  • Experience with CI/CD pipelines and modern DevOps practices
  • Ability to solve problems through code, not just SQL
  • Hands-on experience with modern data engineering technologies, including:
  • Spark / PySpark
  • Databricks
  • Kafka
  • Flink
  • Data Lake architectures
  • Experience building both batch and streaming data solutions

Practical experience delivering solutions on at least one major cloud platform:

  • Amazon Web Services (AWS)

Relevant services may include:

  • Data processing and analytics tools (BigQuery, Synapse, Redshift, Databricks, Dataflow, Glue, EMR, Dataproc)
  • Event streaming platforms (Pub/Sub, Event Hubs, Kinesis)
  • Container platforms (GKE, AKS, EKS)

DevOps & Deployment

Experience with:

  • Docker
  • Infrastructure as Code (Terraform or similar)
  • Monitoring and observability tools

Experience should be gained through real production projects, not certifications alone.

Additional Valuable Skills

  • Data modelling (relational and dimensional)
  • Data warehousing concepts
  • Modern orchestration and data platforms such as Databricks, Kafka and Microsoft Fabric

Ideal Candidate

We're looking for a modern data engineer with a software engineering mindset. Candidates should have proven experience delivering cloud-based data solutions using Python, Spark, CI/CD, Git and modern data platforms. Experience limited to traditional SQL, SSIS or ETL development without modern engineering practices is unlikely to meet current client requirements.

What We Value

  • Continuous learning and professional development
  • Ability to contribute immediately within a modern engineering environment
  • Client-facing consulting experience is advantageous

See also

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