Senior Data Engineer | Azure | Snowflake | Fivetran | DBT | ETL / ELT | APIs

Senior Data Engineer | Azure | Snowflake | Fivetran | DBT | ETL / ELT | APIs Rate: £225 per day (Outside IR35) Contract: Initially 9 months - likely to extend Start: ASAP Working model: Remote depending on location or Hybrid 1 day p/w Working hours: UK (GMT) Required: Azure, Fivetran (Airbyte or Airflow is considered), Snowflake, Python & APIs (Non Negotiable) 🚨 Non‑Negotiables - Please only apply if you have ALL of the following 🚨 Core technologies: • Snowflake (data warehouse) • Fivetran (data connectors) • DBT (data transformation) • Python (including building custom API connectors) Environment: Strong experience working in Azure‑based data environments • Proven, hands‑on experience as a Data Engineer • Strong experience building and maintaining ETL/ELT pipelines • Solid understanding of data warehousing and data modelling concepts Key skills: • Experience with Fivetran, Snowflake, Python, and APIs • Strong knowledge of connecting to APIs for data ingestion • Familiarity with similar tools (Airbyte, Airflow, etc.) acceptable if you understand the core principles of API‑based ingestion • Strong SQL skills and experience with structured and semi‑structured data • Experience ensuring data quality, consistency, and governance • Ability to work UK (GMT) hours • High‑level written and spoken English, with the ability to communicate clearly with a global team Role Overview We’re looking for an experienced Senior Level Data Engineer to join a fast‑moving team responsible for building and scaling a modern, Azure‑native data platform. You’ll play a key role in designing, developing, and maintaining robust data infrastructure that supports analytics, reporting, and business decision‑making across the organisation. This is a hands‑on role focused on data pipelines, ETL/ELT processes, data modelling, and data quality -working closely with analysts, data scientists, and software engineers in a collaborative environment. Key Responsibilities • Design, develop, and maintain data infrastructure including data warehouses, data lakes, databases, and ETL pipelines • Build efficient, scalable ETL/ELT pipelines to ingest data from multiple sources, including API‑based ingestion • Develop custom API connectors in Python where required • Design and implement data models to support business and analytical requirements • Define data schemas, structures, and relationships between data entities • Optimise data models and pipelines for performance, scalability, and reliability • Collaborate with cross‑functional teams to understand data needs and ensure seamless data access and integration • Support system integration efforts to ensure accurate and consistent data flow between platforms • Implement and maintain data quality controls, validation processes, and governance frameworks • Monitor data trends and analyse datasets to identify patterns, risks, and opportunities for improvement • Document data engineering processes, data flows, and system configurations • Clearly articulate complex technical concepts to both technical and non‑technical stakeholders Nice to Have • Experience with modern orchestration tools (e.g., Airflow, Dagster) • Experience with big data technologies or streaming platforms • Exposure to analytics, BI, or data science workflows • Experience working in fast‑paced or scale‑up environments If you tick all of the above boxes and can start ASAP, we’d love to hear from you.