Role - Azure Data Engineer

Rate - £600 per day inside

Hybrid working - 1 day a week onsite (Centre of London)

Duration - Initial 6 months

My client is a large Financial services organisation based out of London and they are going through a huge data transformation that is expected to run for at least 18 months.

My client is seeking experienced Azure Data Engineers for a stakeholder-facing project. This role will have particular emphasis on Azure, Databricks and DevOps. Our client is in the consultancy sector but does not have a preference for previous experience within a consultancy role. There is also a key element of delivery within the project, focusing on delivering technically but also ensuring the quality of delivery within a wider team of Data Engineers. The ideal candidate needs experience and confidence to speak up when several teams can be involved in delivering the project. There is a massive emphasis on Pyspark and Databricks for this particular role.

Technical Skills Required:

• Azure (ADF, Functions, Blob Storage, Data Lake Storage, Logic Apps, DevOps)
• Databricks
• Spark
• Delta Lake
• SQL
• Python
• PySpark
• ADLS

Day To Day Responsibilities:

• Extensive experience in designing, developing, and managing end-to-end data pipelines, ETL (Extract, Transform, Load), and ELT (Extract, Load, Transform) solutions.
• Maintains a proactive approach to staying updated with emerging technologies and a strong desire to continuously learn and adapt to new tools, languages and methodologies in the ever-evolving field of data engineering and analytics.
• Possesses expert knowledge of the contemporary data engineering and analytics landscape, including current tools, pertinent approaches and likely challenges.
• A strong history of designing and constructing databases, analytics systems and Business Intelligence (BI) platforms within the context of Big Data.
• A demonstrable ability to mentor and coach junior data engineers, sharing knowledge and expertise to help them grow in their roles.
• The capability to collaborate efficiently with business stakeholders to understand their requirements and translate them into effective data solutions.
• Strong support for Continuous Integration/Continuous Deployment (CI/CD) practices and an understanding of agile working methodologies.