Azure Data Engineer: Cloud Analytics & ETL Expert

Successfactors; Greater London; Hybrid; GBP 65,000 - 90,000; Full time

Job summary

Reply is seeking a Data Engineer to design, develop, and implement data solutions using Azure services such as Data Factory, Databricks, Synapse Analytics, and Data Lake Storage.

You will collaborate with clients and internal teams to understand requirements, troubleshoot data issues, and deliver robust, scalable analytics solutions while mentoring junior engineers and contributing to team growth.

Qualifications

• Experience in data engineering with Microsoft Azure.
• Hands-on experience with Azure Data Factory, Databricks, Synapse Analytics, and Data Lake Storage.
• Strong Python, Scala, or SQL development background.
• Understanding of data modelling and analytics solutions.
• Ability to work in a customer-facing role, engaging effectively with clients and stakeholders.
• Self-sufficient, with excellent problem-solving and communication skills.

Responsibilities

• Design, develop, and maintain data pipelines using Azure Data Factory and Databricks.
• Implement data models and analytics solutions using Synapse Analytics and Data Lake Storage.
• Collaborate with clients to understand their data needs and provide tailored solutions.
• Develop and optimise ETL/ELT processes to maintain data integrity and performance.
• Ensure data solutions are scalable, resilient, and secure.
• Troubleshoot and resolve data-related issues efficiently.
• Document technical solutions and best practices.
• Mentor junior engineers and contribute to team development.

Skills

Azure Data Factory

Azure Databricks

Synapse Analytics

Data Lake Storage

Python

Scala

SQL

Customer-facing communication

Tools

Logic Apps

Snowflake

BigQuery

Redshift

Terraform

Bicep

PowerShell

CI/CD pipelines

Job description

Reply is seeking a Data Engineer to design, develop, and implement data solutions using Azure services such as Data Factory, Databricks, Synapse Analytics, and Data Lake Storage.

You will collaborate with clients and internal teams to understand requirements, troubleshoot data issues, and deliver robust, scalable analytics solutions while mentoring junior engineers and contributing to team growth.