Azure Data Engineer: Pipelines & Analytics

Reply, Inc.; Manchester; Hybrid; GBP 55,000 - 85,000; Full time

Job summary

Reply, Inc. in Manchester is seeking a Data Engineer to design, develop and deploy data solutions on Microsoft Azure including Data Factory, Databricks, Synapse Analytics and Data Lake Storage.

You will work closely with clients and internal teams to translate requirements into robust data pipelines. The role emphasises mentoring junior engineers, writing clean documentation, and delivering scalable, secure ETL/ELT processes.

Qualifications

• Experience with Microsoft Azure data engineering and cloud analytics.
• Hands-on with Azure Data Factory, Databricks, Synapse Analytics and Data Lake Storage.
• Strong Python, Scala or SQL development background.
• Ability to work in a customer-facing role and communicate with clients.
• Self-sufficient with problem-solving and collaboration 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 data needs and deliver tailored solutions.
• Develop and optimise ETL/ELT processes to maintain data integrity and performance.
• Ensure data solutions are scalable, resilient and secure.
• Troubleshoot data-related issues and document solutions.
• Mentor junior engineers and contribute to team development.
• Document best practices.

Skills

Azure Data Engineering

Python/Scala/SQL

Data Modeling

Client-facing

Tools

Azure Data Factory

Databricks

Synapse Analytics

Data Lake Storage

Snowflake/BigQuery/Redshift

Job description

Reply, Inc. in Manchester is seeking a Data Engineer to design, develop and deploy data solutions on Microsoft Azure including Data Factory, Databricks, Synapse Analytics and Data Lake Storage.

You will work closely with clients and internal teams to translate requirements into robust data pipelines. The role emphasises mentoring junior engineers, writing clean documentation, and delivering scalable, secure ETL/ELT processes.