Edinburgh, Scotland, United Kingdom Hybrid / WFH Options
In Technology Group
knowledge of SQL, Python, and data pipeline tools (e.g., Apache Airflow, dbt). Experience with cloud services (AWS, Azure, or GCP). Familiarity with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery). Excellent problem-solving skills and a collaborative mindset. Nice to Have Experience in consulting or working with multiple clients. Knowledge of DevOps practices and CI/CD More ❯
and customise them for different use cases. Develop data models and Data Lake designs around stated use cases to capture KPIs and data transformations. Identify relevant AWS services - on Amazon EMR, Redshift, Athena, Glue, Lambda, to design an architecture that can support client workloads/use-cases; evaluate pros/cons among the identified options to arrive at More ❯
performing data analytics on AWS platforms Experience in writing efficient SQL's, implementing complex ETL transformations on big data platform. Experience in a Big Data technologies (Spark, Impala, Hive, Redshift, Kafka, etc.) Experience in data quality testing; adept at writing test cases and scripts, presenting and resolving data issues Experience with Databricks, Snowflake, Iceberg are required Preferred qualifications, capabilities More ❯
the 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 … Strong mentoring skills and ability to foster team growth and development Strong understanding of the data engineering lifecycle, from ingestion to consumption Hands-on experience with our data stack (Redshift, Airflow, Python, DVT, MongoDB, AWS, Looker, Docker) Understanding of data modelling, transformation, and orchestration best practices Experience delivering both internal analytics platforms and external data-facing products Knowledge of More ❯
