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Company Description
Danoa helps small and mid-sized businesses turn scattered, underused data into clear, actionable insight without needing an in-house data team. The company designs centralized dashboards in Power BI and Tableau, along with custom data pipelines and lightweight data products that automate everyday data work. Danoa also delivers practical, non-overengineered AI solutions that give small teams outsized value and faster decisions. Focused on affordability and speed, Danoa closes the gap for organizations that have lots of data but limited time, budget, or dedicated expertise to use it effectively.
Role Description
In this full-time, on-site Data Engineer role based in Coventry, the team member will design, build, and maintain scalable data pipelines that integrate data from multiple business systems. The role involves developing and optimizing ETL workflows, modeling data for analytics and reporting, and supporting the creation of robust data warehouses and data marts. The Data Engineer will collaborate closely with analytics and product teams to ensure data structures align with dashboarding, reporting, and AI solution needs. Day-to-day responsibilities include:
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- Monitoring data quality
- Troubleshooting pipeline issues
- Improving performance
- Documenting data processes and standards for internal stakeholders
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Qualifications
- Strong data engineering skills, including experience designing and implementing data pipelines and working with modern data engineering tools and frameworks.
- Solid data modeling and data warehousing skills, including the ability to design schemas that support reporting, BI, and scalable storage.
- Hands-on experience with Extract Transform Load (ETL) processes, including building, scheduling, and optimizing ETL jobs across multiple data sources.
- Data analytics skills, with the ability to translate business requirements into data structures that support dashboards, reports, and exploratory analysis.
- Experience with BI tools (e.g., Power BI, Tableau) and SQL databases; familiarity with cloud data platforms (such as Azure, AWS, or GCP) is beneficial.
- Proficiency in at least one programming language commonly used in data engineering (e.g., Python, Scala, or Java) and comfort with version control tools.
- Strong problem-solving skills, attention to data quality and reliability, and the ability to communicate clearly with both technical and non-technical stakeholders.
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent practical experience; prior work with small or mid-sized businesses is a plus.
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