What you’ll do

📍Participate in building and operating a data platform that empowers everyone in the company, ensures performance and reliability, and with user-friendliness always in mind. 📍Shape to the ongoing design of our core data model to support advanced analytics and reporting and define data quality, governance, and lifecycle standards with clear processes and documentation. 📍Design, implement, and maintain robust, observable data pipelines for ingestion and transformation and applying solid engineering practices (testing, code reviews, CI/CD, versioning) 📍Partner with stakeholders across product, operations, finance, risk/compliance, and engineering to turn business goals into pragmatic, measurable data solutions. 📍Contribute to team strategy and roadmapping to align the team’s technical efforts with broader organisational goals.

Who you are

📍You build production-grade dataflows with Python and SQL, schedule/operate them with Airflow or Dagster, and model/test transformations in dbt. 📍You’re comfortable in AWS (GCP/Azure welcome) and provision cloud resources in code with Terraform (or similar). 📍You operate Snowflake thoughtfully, structure roles and permissions, optimise performance and cost 📍You understand data quality and governance fundamentals (validation, documentation, lineage, privacy). 📍You bring a growth mindset and willingness to learn with additional bonus points if you have experience with: Kubernetes, Kafka, event collection platform (RudderStack/Segment), data catalogs (DataHub), Apache Iceberg (or other open table formats), and A/B testing/feature flags.

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