Data Engineer

Amana Group; Abu Dhabi; On-site; AED 210,000 - 330,000; Full time

Job summary

Amana Group in the United Arab Emirates seeks a Data Engineer to design and deliver end-to-end data products across multiple domains. You will build robust data ingestion from enterprise systems, lead Databricks-based pipelines, and implement data quality and governance controls.

You will mentor peers and partner with data scientists to enable AI-ready data assets. You will own operational health, apply DataOps practices, and contribute to reusable frameworks while delivering Power BI semantic

Qualifications

• 5+ years hands-on data engineering experience with Databricks, Spark and Delta Lake in production.
• Experience integrating enterprise sources such as Oracle Fusion, SAP, Microsoft Dynamics, or CMiC, including incremental and API-based extraction.
• Data quality and access controls implemented via Unity Catalog, Purview, or equivalent tooling.
• Strong SQL, Python, and PySpark with Git-based CI/CD delivery (Azure DevOps or equivalent).
• Excellent written and verbal communication across technical and business audiences.

Responsibilities

• Design and deliver end-to-end data products across assigned business domains.
• Lead migrations within Synapse Analytics to Databricks and re-engineer pipelines, manage parallel loads, and prepare for cutover.
• Contribute reusable data engineering frameworks, templates and patterns; propose improvements to standards.
• Implement data quality, governance controls, and data-health monitoring across domains.
• Own the operational health of domains: monitoring, alerting, incident response and root-cause fixes.
• Build AI-ready data products, feature tables and document pipelines for ML use cases with Data Scientist and AI Engineer.
• Deliver Power BI semantic models and certified datasets supporting self-service adoption.

Skills

Data engineering

Databricks

Apache Spark

Delta Lake

SQL

Python

PySpark

Git CI/CD

Azure DevOps

Communication

Tools

Databricks

Apache Spark

Delta Lake

Unity Catalog

Microsoft Purview

Power BI

Azure DevOps

Git

Job description

Data Engineer Data Product Design amp Delivery

Design and deliver end-to-end data products for assigned business domains across the bronze silver and gold layers including the dimensional and semantic models that serve reporting and AI

Build robust ingestion from Amana s enterprise systems Oracle Fusion Finance HCM P2P CRM Hyperion CMiC project and operations systems SharePoint and Power Platform using change data capture incremental and API-based patterns

Lead workstreams within the Synapse Analytics to Databricks migration re-engineering pipelines running parallel loads reconciling results and preparing for cutover

Contribute reusable frameworks templates and patterns and propose improvements to the standards owned by the Data Engineering Lead Data Architect

Implement data quality frameworks monitoring and reconciliation across your domains and drive issues to resolution at source with data owners

Implement access control lineage classification and data-handling rules in Unity Catalog and Microsoft Purview including PDPL controls for personal and HR data

Partner with the Data Governance Office to turn domain policies into working controls and documented certified datasets

Tune Spark and SQL workloads for performance and cost within the platform s cluster and workload policies

Own the operational health of your domains monitoring alerting incident response and root-cause fixes

Apply CI CD automated testing and DataOps practices using Git and Azure DevOps

Build AI-ready data products feature tables and document and vector pipelines for machine learning RAG and agent use cases in partnership with the Data Scientist and AI Engineer

Deliver Power BI semantic models and certified datasets with the Data Analyst supporting self-service adoption through the Amana Digital Academy

Apply AI-assisted engineering code generation testing documentation and lineage discovery with appropriate human review and help the team adopt it safely

Translate requirements from finance project and operations stakeholders into technical designs with clear delivery outcomes

Mentor Data Engineers through pairing design reviews and code review

Explain design choices trade-offs and risks clearly to technical and business audiences

Required Qualifications

• 5+ years of hands-on data engineering experience, including at least 2 years with Databricks, Apache Spark, and Delta Lake in production. Designed and delivered end-to-end data products from ingestion to modelled, consumable data for one or more business domains. Experience integrating complex enterprise sources such as Oracle Fusion, SAP, Microsoft Dynamics, or CMiC, including incremental and API-based extraction. Data quality and access controls implemented in practice using Unity Catalog, Microsoft Purview, or equivalent tooling. Strong SQL, Python, and PySpark, with Git-based CI/CD delivery (Azure DevOps or equivalent). Excellent written and verbal communication skills across technical and business audiences.

Preferred (one or more)

• Databricks Certified Generative AI Engineer Associate
• Microsoft Certified: Fabric Data Engineer Associate (DP-700)
• Microsoft Certified: Fabric Analytics Engineer Associate (DP-600)
• Microsoft Certified: Azure Data Engineer Associate (DP-203 retired 2025; accepted if held)

Required (held, or achieved after joining within the period shown)

• Databricks Certified Data Engineer Associate or Microsoft Certified: Azure Databricks Data Engineer Associate (DP-750) within 6 months
• Databricks Certified Data Engineer Professional within 12 months