e.g. GDPR compliance) Proficiency in ELT/ETL processes Strong experience in data ingestion, transformation & orchestration technology (ETL tools such as Informatica, Datastage, SSIS, etc ) or open source Meltano, Airbyte, and Airflow Proven experience with DBT (data build tool) Proficiency with business intelligence tools (Power BI, Tableau, SAP BI, or similar). Integration & Programming Hands-on experience with API development More ❯
products are recognised by industry leaders like Gartner's Magic Quadrant, Forrester Wave and Frost Radar. Our tech stack: Superset and similar data visualisation tools. ETL tools: Airflow, DBT, Airbyte, Flink, etc. Data warehousing and storage solutions: ClickHouse, Trino, S3. AWS Cloud, Kubernetes, Helm. Relevant programming languages for data engineering tasks: SQL, Python, Java, etc. What you will be doing More ❯
managing a team of Data Engineers Experience with Data modelling, Data warehousing, and building ETL pipelines Experience with AWS (S3, EKS, EC2, RDS) or similar cloud services, Snowflake, Fivetran, Airbyte, dbt, Docker, Argo Experience in SQL, Python, and Terraform Experience with building Data pipelines and applications to stream and process datasets Robust understanding of DevOps principles is required Experience managing More ❯
inform strategic decisions both at the Board/Executive level and at the business unit level. Key Responsibilities Design, develop, and maintain scalable ETL pipelines using technologies like dbt, Airbyte, Cube, DuckDB, Redshift, and Superset Work closely with stakeholders across the company to gather data requirements and setup dashboards Promote a data driven culture at Notabene and train, upskill power More ❯
and pipeline development Experience with IaC tools such as Terraform or Ansible for deployment and infrastructure management Hands-on experience with; ETL/ELT orchestration and pipeline tools (Airflow, Airbyte, DBT, etc.) Data warehousing tools and platforms (Snowflake, Iceberg, etc.) SQL databases, particularly MySQL Desired Experience: Experience with cloud-based services, particularly AWS Proven ability to manage stakeholders, their expectations More ❯
a Senior Data Warehouse Engineer, you'll: Help redesign and modernise the existing data warehouse using ELT best practices. Migrate legacy ETL workflows to modern tools like Fivetran (or Airbyte) and dbt. Optimise data models in Amazon Redshift for performance, scalability, and cost-effectiveness. Replace legacy orchestration scripts with Python or Bash for enhanced automation. Enforce best practices for data More ❯
services (S3, Redshift, Lambda) including data storage, computation, and security. Experience with BI tools such as Power BI, AWS Quicksight Familiarity with open-source data-stack tools (Airflow, DBT, Airbyte) Good understanding of software development best practices, CI/CD Experience in performance tuning and optimization. Strong experience with automation, testing, and CI/CD pipelines in data engineering. Excellent More ❯
data-focused backend services Have hands-on experience with cloud infrastructure (GCP/AWS/Azure), infrastructure-as-code (Terraform), containerisation (Docker/k8s) and data pipelines (SQL, dbt, Airbyte) Love automation, process improvement and finding ways to help others work efficiently Are comfortable working autonomously and taking responsibility for the delivery of large technical projects Are eager to learn More ❯
Excellent communication skills - able to simplify technical concepts for non-technical stakeholders Nice-to-Have: Experience working in client-facing consultancy projects Knowledge of modern data stack tools (Fivetran, Airbyte, Stitch) Python for data transformation or automation Familiarity with Git and version control best practices If you would like to be considered for the Analytics Consultant role and feel you More ❯
Prometheus. We're in the process of transitioning to OpenTelemetry and Honeycomb for our application telemetry (traces and metrics). - We manage a data pipeline using Pub/Sub, Airbyte, and dbt. Our Current Focus We're currently driving a big shift in how we think about and monitor reliability across the engineering organisation, with a focus on early detection More ❯
