About The Role

Join our team as a Senior Data Engineer, where you'll be responsible for the technical direction, platform design, and architectural decision-making of modern, cloud-native data platforms. You'll work closely with clients to understand their problems and shape solutions, while also setting engineering standards and best practices across teams. This is a hands-on role that requires deep experience with Spark, modern data platforms, and cloud data services.

Design and build greenfield data platforms, real-time pipelines, and data products for clients.
Own the end-to-end architecture of modern, cloud-native data platforms, making high-impact architectural decisions.
Act as a trusted technical advisor, translating business needs into pragmatic engineering decisions and shaping solutions.
If you enjoy solving hard data problems, shaping modern architectures (data mesh, data products, contracts), and delivering real outcomes — this is your lane
Deep experience with Spark and modern data platforms (Databricks / Snowflake)
Solid grasp of cloud data services (AWS or GCP)
Strong Python and SQL
Strong data modelling skills and architectural decision-making ability
Infrastructure-as-code experience (Terraform, Pulumi)
CI/CD pipelines using tools like GitHub Actions, ArgoCD
Demonstrated ownership of large-scale data platform architectures
Comfortable balancing trade-offs between performance, cost, and complexity
Data testing and quality frameworks (dbt, Great Expectations, Soda)
Strong consulting instincts — able to challenge assumptions and guide clients toward better outcomes
Built and operated large-scale data pipelines in production
Comfortable with multiple storage technologies and formats
Experience in consulting or professional services environments
If you’re a senior data engineer who wants to build properly, think clearly, and deliver real outcomes - we should talk
Comfortable mentoring senior engineers and influencing technical culture
Strong data modelling capability and architectural judgement

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