Azure Data Engineer: Pipelines, DW & BI (Remote)

Version 1

United Kingdom

Remote

GBP 55,000 - 75,000

Full time

2 hours ago

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Benefits offered by this job

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Flexible/Remote

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Job summary

Version 1 is seeking an experienced Data Specialist to support delivery, enhancement and ongoing development of enterprise data and analytics solutions within the UK. You will work closely with project teams, business units and technical staff to analyse data, develop reporting, and drive strategic data initiatives using Azure Data Factory, Synapse and Power BI.

The role requires strong SQL, data engineering and data modelling skills, a lead-capacity track record, and collaborative, agile

Qualifications

4–6 years' experience in Data Specialist/Data Engineering or closely related role.
At least 2 years' experience operating in a lead capacity.
Strong hands-on experience with Azure Data Factory.
Strong experience with Azure Synapse.
Strong experience with Power BI or equivalent BI/reporting technologies.
Advanced SQL and database experience.
Experience using Python for data manipulation and analysis.
Strong understanding of ETL/ELT processes and data pipelines.
Experience designing and developing data warehouses and data architectures.
Strong data modelling experience, including working with complex datasets.

Responsibilities

Design, develop and maintain scalable data pipelines, data models and data warehouse solutions.
Build and support ETL/ELT processes that integrate data from multiple source systems.
Develop and maintain solutions using Azure Data Factory, Azure Synapse and Power BI.
Analyse complex datasets to identify trends, anomalies and actionable insights.
Develop dashboards, reports and analytics solutions to support business and operational decision-making.
Design and optimise complex data models and datasets.
Use Python and SQL for data manipulation, transformation and analysis.
Support and enhance existing data solutions as they scale.
Optimize code, queries, pipelines and processes for performance and reliability.
Perform root cause analysis on data quality and data processing issues.
Identify opportunities to reuse and improve existing data flows and solutions.
Use Azure DevOps, including Boards, Repos, Pipelines and Test Plans, to support development and delivery.
Design and implement appropriate build, release, deployment and configuration processes.
Apply data standards, governance and best practices, including GDPR requirements.
Work collaboratively within an Agile delivery environment.