👨🏻‍💻 postech.work

Data Engineer

Candour • 🌐 In Person

In Person Posted 4 days, 11 hours ago

Job Description

Data Engineer (Azure SQL and Cosmos DB)

📍 Wigan / Hybrid (Tues \& Thurs office days)

Job Summary

Own and optimise the company’s cloud data platform, with primary responsibility for Azure SQL and Cosmos DB. Ensure high performance, availability, security, and integrity across production and non-production environments. Lead data migration initiatives and oversee reliable, secure data operations in a modern Azure environment.

Key Responsibilities

Database Ownership:

Design, configure, and manage Azure SQL and Cosmos DB (sizing, indexing, partitioning, backup/restore, high availability).

Performance \& Reliability:

Proactively monitor and tune performance; implement robust backup, disaster recovery, and incident response processes.

Security \& Compliance:

Apply best practices for access control, encryption, auditing, and data protection, supporting ISO27001 and related standards.

Data Migration \& ETL:

Lead end-to-end data migrations from third-party/client systems, including mapping, transformation, validation, and cutover planning. Build and maintain data pipelines using Azure Data Factory.

Data Quality \& Governance:

Maintain strong data integrity, documentation, and operational standards across environments.

Collaboration:

Work closely with Architecture, Development, Operations, and Delivery teams to support scalable, secure data solutions.

Skills \& Experience

Strong DBA/Data Engineering experience with Azure SQL and Cosmos DB (or similar cloud platforms).

Proven expertise in performance tuning, operational database management, and security.

Hands-on experience delivering data migrations and building ETL/ELT pipelines (ideally with Azure Data Factory).

Understanding of how applications (e.g., .NET) interact with databases.

Personal Attributes

Detail-oriented with strong ownership of data quality and reliability.

Calm and methodical under pressure.

Collaborative and proactive in improving performance, cost efficiency, and data practices.

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