£550 Per day
Inside
Remote
United Kingdom
Summary: The role is for a Data Engineer with strong hands-on experience in Microsoft Fabric, focusing on data engineering tasks such as building and maintaining data pipelines. The position requires proficiency in Python and SQL, along with a good understanding of data modeling and cloud technologies. The contract is remote and requires SC clearance, with an initial duration until March 2026.
Key Responsibilities:
- Develop and maintain scalable ETL/ELT pipelines using cloud technologies.
- Utilize Microsoft Fabric, including spark notebooks, pipelines, and data flows.
- Transform and model data using strong SQL skills (T-SQL or similar).
- Implement data engineering best practices, including version control and CI/CD pipelines.
- Ingest data using REST APIs and SFTP.
- Create dashboards using PowerBI.
- Maintain data pipelines and ensure data integrity.
Key Skills:
- Strong hands-on experience with Microsoft Fabric.
- Proficient in Python for data engineering (Pandas, PySpark, asyncio).
- Strong SQL skills (T-SQL or similar).
- Experience with cloud technologies for ETL/ELT.
- Good understanding of data modeling (star/snowflake) and data warehousing.
- Familiarity with version control (Git) and CI/CD pipelines.
- Knowledge of REST APIs and SFTP data ingestion.
- Experience with PowerBI for dashboarding.
- Some knowledge of LLMs, especially Azure AI.
Salary (Rate): £550 daily
City: undetermined
Country: United Kingdom
Working Arrangements: remote
IR35 Status: inside IR35
Seniority Level: undetermined
Industry: IT
Daily rate: £500 to £550 inside IR35
Must be SC Cleared
Location: Remote - UK based only
Duration: initial contract until end for March 2026
Experience: Strong hands-on experience with Microsoft Fabric (spark notebooks, pipelines, data flows). Proficient in Python for data engineering (eg, Pandas, PySpark, asyncio, automation scripts). Strong SQL skills (T-SQL or similar) for transforming and modelling data. Experience building scalable ETL/ELT pipelines using cloud technologies. Good understanding of data modelling (star/snowflake), data warehousing, and modern data lakehouse principles. Familiarity with version control (Git) and CI/CD pipelines
The main skillset is Data engineering - specifically experience in ingesting and maintaining data pipelines. Knowledge of REST APIs, SFTP data ingestion is useful. PowerBI for dashboarding Some knowledge of LLMs would be useful - especially Azure AI