Data Engineer

The Job Holder is Responsible to Builds and maintains data pipelines, ETL/ELT processes, and data integration solutions that move and transform data across the data platform to support analytics, reporting, and AI applications.

Description

Deliverables

Pipeline Success Rate ≥99%

Data Freshness SLA Meets agreed refresh schedule

Data Quality Score ≥95%

Pipeline Documentation 100%

Incident Response ≤2 hours for pipeline failures

• Know How (applying of knowledge & skills in job tasks)

Description

Data Pipeline Development

• Design, build, and maintain ETL/ELT pipelines using Azure Data Factory, Synapse, or Databricks.
• Integrate data from D365 ERP, POS, e-commerce, and external sources into the data warehouse.
• Monitor pipeline performance and resolve data failures promptly.

Data Quality

• Implement data quality checks and validation within pipelines.
• Collaborate with Data Analysts and BI Developers to resolve data issues.
• Maintain data lineage and documentation for all pipelines.

Note: The principal accountabilities listed above are an illustrative list and not an exhaustive list. Additional responsibilities may be added from time to time depending on organizational requirements.

 Minimum Qualification

­ Bachelor degree in Computer Science, Data Engineering, or IT.

­ Certified in Azure Data Engineer Associate preferred

 Minimum Experience

­ Minimum Experience of 3–5 years in data engineering.

 Other Requirement (Skills Set)

­ Azure Data Factory, Synapse Analytics, Databricks

­ SQL, Python, Spark for data transformation

­ D365 data integration: OData, Data Integrator, dual write

­ Data quality and testing in pipelines

­ Git and Azure DevOps for pipeline code management

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