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This job expired on 19/07/2026. It no longer accepts applications.
Senior Data Engineer
N-iX
Job description
About the role
You will join the Data Platform team of a global mining organization, designing and delivering a modern Azure-native data infrastructure. The role is hands-on, focusing on building and maintaining robust pipelines that feed analytics across finance, operations and supply chain.
Key responsibilities
- Gather and analyse business requirements to define integration priorities.
- Design, build and maintain scalable data pipelines with Azure Data Factory.
- Develop and optimise transformation logic in Azure Synapse Analytics (dedicated and serverless SQL pools, Synapse Pipelines).
- Create and manage Databricks notebooks and jobs using PySpark / Spark SQL for large-scale processing and feature engineering.
- Implement reliable API extraction from REST and SOAP services, handling pagination, OAuth 2.0, API keys, rate limiting and error recovery.
- Design and maintain a lakehouse architecture (raw, curated, serving layers) on Azure Data Lake Storage Gen2.
- Ensure data quality through validation frameworks, monitoring, alerting and lineage documentation.
- Collaborate with analytics engineers and data consumers to model data for downstream use.
- Apply CI/CD, infrastructure-as-code (Azure DevOps, Terraform/Bicep) and manage environments.
- Participate in data governance, metadata management and access control.
Required profile
- 4+ years of experience in data engineering or a closely related software engineering role.
- Strong analytical and communication skills.
- Ability to work autonomously in a distributed team.
Required skills
- Azure Data Factory – pipelines, triggers, linked services, data flows.
- Azure Synapse Analytics – SQL pools, Synapse Pipelines, ADLS Gen2 integration.
- Azure Databricks – PySpark, Delta Lake, job clusters (Unity Catalog a plus).
- API extraction – REST, SOAP, OAuth 2.0, API keys, pagination, error handling.
- SQL (T‑SQL or Spark SQL) and Python for data manipulation.
- Data modelling – star/snowflake, data vault, medallion architecture.
- Azure DevOps, Git, CI/CD pipelines, Terraform/Bicep.
- Data security – RBAC, encryption in Azure.
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