of experience in data engineering or a related field, with a focus on building scalable data systems and platforms. Expertise in modern data tools and frameworks such as Spark, dbt, Airflow, Kafka, Databricks, and cloud-native services (AWS, GCP, or Azure) Understanding of data modeling, distributed systems, ETL/ELT pipelines, and streaming architectures Proficiency in SQL and at least More ❯
love to talk to you if: You've led technical delivery of data engineering projects in a consultancy or client-facing environment You're experienced with Python, SQL, .NET, dbt, Airflow and cloud-native data tools (AWS, GCP or Azure) You have strong knowledge of data architecture patterns - including Lakehouse and modern warehouse design (e.g. Snowflake, BigQuery, Databricks) You know More ❯
data platform, including data pipelines, orchestration and modelling. Lead the team in building and maintaining robust data pipelines, data models, and infrastructure using tools such as Airflow, AWS Redshift, DBT and Looker.Ensuring the team follows agile methodologies to improve delivery cadence and responsiveness. Contribute to hands-on coding, particularly in areas requiring architectural input, prototyping, or critical delivery support. Support More ❯
