Data Engineer

Amana Group; United Arab Emirates; Sur place; AED 320 000 - 640 000; Plein temps

Résumé du poste

Amana Group in the United Arab Emirates seeks an experienced Data Engineer to design end-to-end data products across multiple layers and enterprise sources. You will build robust ingestion from Oracle Fusion, SAP, CMiC, and more, and lead migration efforts in Synapse Analytics to Databricks.

You will implement data quality, governance, and security controls, optimize Spark/SQL performance, and enable AI/Analytics by delivering feature tables and AI-ready datasets in collaboration with data

Qualifications

• 5+ years hands-on data engineering experience, incl. 2+ years with Databricks, Spark, Delta Lake in production.
• Designed and delivered end-to-end data products for one or more business domains.
• Experience integrating enterprise sources such as Oracle Fusion, SAP, Microsoft Dynamics, or CMiC, incl. incremental and API-based extraction.
• Data quality and access controls implemented 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 across technical and business audiences.
• Required certifications: Databricks Certified Data Engineer Associate or Microsoft Azure Databricks DP-750; Databricks Professional within 12 months; Fabric DP-700/DP-600/DP-203 (retired) as applicable.

Connaissances

SQL

Python

PySpark

Communication

Analytical thinking

Formation

Bachelor's degree in Computer Science or related field

Databricks Certified Data Engineer Associate (DP-750) within 6 months

Databricks Certified Data Engineer Professional within 12 months

Microsoft Certified: Azure Databricks Data Engineer Associate (DP-203) – within 6 months (retired 2025; accepted if held)

Fabric Data Engineer Associate (DP-700) or Fabric Analytics Engineer Associate (DP-600) preferred

Outils

Databricks

Apache Spark

Delta Lake

Azure DevOps

Git

Description du poste

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).

Data Quality, Governance & Security

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.

Performance, Reliability & Cost

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.

Analytics & AI Enablement

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.

Qualifications

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.

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

Preferred (one or more):

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)