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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data & Analytics Engineer - **Company:** Hackajob Ltd - **Location:** London, UK (Remote available) - **Experience:** Expert - **Salary:** £85,000.0 - **Contract:** Permanent contract - **Skills:** Sql Data Warehouse, Application Programming Interfaces (APIs), Airflow, Amazon Web Services, Data Analysis, Microsoft Azure, Big Data, BigQuery, Cloud Computing, Cloud Storage, Databases, Continuous Integration, Data Warehousing, DevOps, Python (Programming Language), Operational Databases, Scrum Methodology, Standard Sql, SQL Databases, Workflow Management Systems, Sql Optimization, Delivery Pipeline, Snowflake, Data Analytics, Data Management, Data Pipelines, Amazon Redshift - **Published:** August 22, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5852366024 ## About the Role * Strong experience building and maintaining analytics pipelines using SQL-first transformation patterns, ideally with dbt * Solid understanding of data warehousing concepts, including how dimensional and analytical models are used downstream * Advanced SQL skills, with the ability to write, read, and optimise complex queries across large datasets * Experience working with a cloud data warehouse such as Snowflake, BigQuery, Redshift, or Synapse * Experience working in a modern cloud environment such as AWS, GCP, or Azure, with exposure to core services such as cloud storage and orchestration * Experience working in an Agile delivery environment such as Scrum and/or Kanban * Strong communication skills and the confidence to work directly with stakeholders at all levels * Experience contributing to or supporting data ingestion pipelines, including APIs and event-driven data sources * Familiarity with orchestration tools such as Airflow and ELT architectures * Experience implementing or working with data CI/CD pipelines, such as dbt tests, deployment pipelines, or automated checks * Working knowledge of Python for data-related tasks, automation, or light engineering work * An interest in data quality, observability, and analytics engineering best practices ## Description * Build and maintain analytics-ready data models in our cloud data warehouse, transforming raw and curated data into trusted, well-documented datasets for business and analytical use * Implement complex data models and transformations using SQL and dbt, with a strong understanding of how upstream transformations feed downstream analytical use cases * Work with existing enterprise data models and dimensional structures, extending them to support new analytics requirements * Own and contribute to the enterprise data warehouse, including dimensional models and analytical data sets for both technical users and non-technical business stakeholders * Collaborate with data engineers on the ingestion and orchestration of data from databases, flat files, APIs, and event-driven feeds, ensuring downstream analytics requirements are considered early * Work closely with analytics, data science, and visualisation teams to ensure data products are fit for purpose, performant, and trusted * Support production data assets, including monitoring, issue resolution, and continuous improvement * Help drive a data-first culture through data enablement activities, analytics best practices, and knowledge sharing across the data community * Act as a senior technical contributor within the team, influencing standards, patterns, and ways of working Technologies: * Airflow * AWS * Redshift * Azure * BigQuery * CI/CD * Cloud * Data Warehouse * GCP * Support * Kanban * Python * SQL * Snowflake * dbt * DevOps ## Related Videos - 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