Kennedy Pearce recruits skilled Data Engineers who design, build, and maintain scalable data infrastructure and pipelines to support analytics, business intelligence, and machine learning initiatives.
Typical responsibilities for Data Engineer roles include:
Designing and developing robust data pipelines for batch and real-time data processing
Building and managing data warehouses, lakes, and cloud-based data architectures (e.g. AWS, Azure, GCP)
Writing complex SQL queries and using tools like Apache Spark, Kafka, or Airflow for ETL/ELT workflows
Integrating data from various sources including APIs, databases, and third-party platforms
Optimising data quality, integrity, and consistency across the organisation
Collaborating with data analysts, scientists, and software engineers to ensure accessible and accurate data delivery
Implementing data governance, compliance, and security best practices
Monitoring performance and automating data workflows for scalability and efficiency
Supporting the development of data models, schemas, and metadata management
Kennedy Pearce places Data Engineers with strong technical foundations and a deep understanding of modern data ecosystems to power data-driven decision-making.
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