Technical skills
Job Details
Position Title: Data Engineer
Reports to: Data and AI Manager
Business Line/ Department: Data and Automation/it
3. Job Purpose
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.
- Job Deliverables
- Accountability
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.
Requirements
- 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.
6. Qualifications, Experience
- 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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