Senior Data Engineer

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Data EngineerData

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Quick Summary

Key Responsibilities

Design and develop batch and streaming data pipelines using Azure Data Factory, Fabric Data Factory, notebooks and related services. Build curated lakehouse,

Requirements Summary

Significant data-engineering experience with SQL and Python or PySpark. Hands-on experience with Microsoft Fabric or Azure services such as Data Factory, Data Lake Storage,

Technical Tools

Data EngineerData

Responsibilities

~1 min read

→Design and develop batch and streaming data pipelines using Azure Data Factory, Fabric Data Factory, notebooks and related services.
→Build curated lakehouse, warehouse and semantic data layers that support analytics and AI use cases.
→Implement data-quality checks, metadata, lineage, monitoring, alerting and operational support.
→Optimise pipelines and storage for reliability, security, performance and cost.
→Apply source control, automated testing and CI/CD through Azure DevOps or GitHub.
→Own delivery of your workstreams end-to-end — from design through to production, managing risk and stakeholders along the way
→Set the bar for engineering quality — reviewing designs, shaping standards, and mentoring the team to raise the floor, not just the ceiling.

Requirements

~1 min read

Significant data-engineering experience with SQL and Python or PySpark.
Hands-on experience with Microsoft Fabric or Azure services such as Data Factory, Data Lake Storage, Synapse Analytics and Databricks.
Knowledge of dimensional modelling, lakehouse patterns, medallion architecture and data integration.
Experience with identity, access control, data protection and production support.
Demonstrated ability to own technical workstreams and communicate design decisions clearly to both technical and non-technical audiences.

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