Principal Data Engineer

• Own the end-to-end architecture of modern, cloud-native data platforms
• Design scalable data ecosystems using data mesh, data products, and data contracts
• Make architectural decisions across ingestion, storage, processing, and access layers
• Ensure platforms are secure, compliant, and production-grade
• Design and deliver cloud-native data platforms using Databricks, Snowflake, AWS, and GCP
• Integrate with client systems to enable scalable, consumer-oriented data access
• Build and optimise batch and real-time pipelines
• Work with Kafka, Flink, Kinesis, and Pub/Sub
• Orchestrate workflows using Airflow, Dataflow, and Glue
• Process and transform large datasets using Spark and Flink
• Work across relational, NoSQL, and analytical stores including Postgres, BigQuery, Snowflake, Cassandra, and MongoDB
• Optimise storage formats and access patterns including Parquet, Delta, ORC, and Avro
• Implement secure, compliant data solutions with security by design
• Embed data governance while maintaining developer velocity
• Work directly with clients to understand problems and shape solutions
• Translate business needs into pragmatic engineering decisions
• Act as a trusted technical advisor
• Set engineering standards, patterns, and best practices
• Review designs and code, providing technical direction and mentorship
• Improve data quality, testing, observability, and operational excellence

• Strong Python and SQL
• Deep experience with Spark and modern data platforms (Databricks / Snowflake)
• Solid grasp of cloud data services (AWS or GCP)
• Demonstrated ownership of large-scale data platform architectures
• Strong data modelling skills and architectural decision-making ability
• Ability to balance trade-offs between performance, cost, and complexity
• Experience building and operating large-scale data pipelines in production
• Experience with multiple storage technologies and formats
• Infrastructure-as-code experience with Terraform or Pulumi
• CI/CD pipeline experience using tools such as GitHub Actions or ArgoCD
• Experience with data testing and quality frameworks such as dbt, Great Expectations, or Soda
• Experience in consulting or professional services environments
• Ability to challenge assumptions and guide clients toward better outcomes
• Comfortable mentoring senior engineers and influencing technical culture

• Interesting, high-impact problems
• Opportunity to build modern platforms rather than maintain legacy systems
• Work alongside senior engineers
• Autonomy and influence
• Room to grow