Data Engineer

Arada; Dubai; On-site; AED 350,000 - 550,000; Full time

Job summary

Arada is seeking a Data Engineer – Data & AI with 8+ years of enterprise experience to own end-to-end data solutions, spanning source systems, data integration, lakehouse/warehouse, analytics, and AI enablement.

Responsibilities include building data pipelines, integrating with Dynamics 365, Salesforce, REST APIs, and creating Power BI semantic models. Expect collaboration with BI, IT, and business stakeholders in a large real estate-focused organization.

Qualifications

• 8+ years of professional experience in Data Engineering, Data Integration, or Data Warehousing.
• Extensive hands-on experience with SQL and Python.
• Experience with Databricks, Delta Lake, PySpark and modern data architectures.

Responsibilities

• Design, develop, and maintain enterprise-scale data pipelines for batch, incremental, and real-time data integration.
• Integrate data from Dynamics 365, Salesforce, SQL databases, REST APIs, JSON/CSV files and more.
• Build scalable data solutions using SQL, Python, Databricks, Delta Lake, and Azure Data Factory.

Skills

SQL

Python

Databricks

Data Warehousing

Data Integration

Data Lakehouse

Power BI

Tools

Databricks

Delta Lake

PySpark

Microsoft Fabric

Azure Data Factory

REST APIs

Job description

Role Overview:

We are looking for a Data Engineer – Data & AI with 8+ years of strong enterprise-level experience in modern data engineering, data integration, data warehousing, and cloud data platforms.

Role Overview:

We are looking for a Data Engineer – Data & AI with 8+ years of strong enterprise-level experience in modern data engineering, data integration, data warehousing, and cloud data platforms. This is primarily a Data Engineering role, with additional opportunities to work on Power BI Semantic Models, Generative AI, LLMs, and modern AI solutions. The candidate will take end-to-end ownership of data solutions — from source systems and data integration through data processing, Lakehouse, Data Warehouse, analytics, and AI enablement, to deployment, monitoring, optimization, and production support.

Key Responsibilities

• Design, develop, and maintain enterprise-scale data pipelines for batch, incremental, and real-time/near-real-time data integration.
• Integrate data from Dynamics 365, Salesforce, SQL databases, REST APIs, JSON/CSV files, file systems, and other enterprise applications.
• Build scalable data solutions using SQL, Python, PySpark, Databricks, Delta Lake, Microsoft Fabric, Azure Data Factory, and Notebooks.
• Design and maintain modern Data Lake, Lakehouse, One Lake, Delta Lake, and Enterprise Data Warehouse solutions.
• Implement CDC, incremental loads, MERGE/UPSERT, data quality, validation, reconciliation, monitoring, logging, error handling, and data observability.
• Optimize SQL queries, Spark jobs, Databricks workloads, Delta Lake, and data pipelines for performance, scalability, and reliability.
• Own the complete lifecycle: requirement → architecture → development → testing → deployment → monitoring → troubleshooting → optimization.
• Build trusted data foundations for Power BI, Semantic Models, enterprise analytics, AI, and business applications.
• Work with Power BI Semantic Models, datasets, relationships, measures, and DAX as an added capability.
• Contribute to AI/Generative AI solutions using Azure OpenAI, Azure AI Search, LLMs, RAG, embeddings, vector/semantic search, AI Agents, Data Agents, and enterprise chatbots.
• Integrate AI solutions with enterprise Data Warehouses, Lakehouse’s, APIs, databases, and Semantic Models.
• Work closely with Data Teams, BI Developers, Application Teams, IT, and Business stakeholders.
• Establish reusable engineering frameworks, coding standards, data quality practices, and production support processes.
• Provide technical guidance and mentoring to other team members.

Required Skills & Experience

• 8+ years of professional experience in Data Engineering, Data Integration, or Data Warehousing.
• Very strong hands-on expertise in SQL and Python.
• Strong experience with SQL Server, Databricks, Delta Lake, PySpark.
• Hands-on experience with Microsoft Fabric and/or Azure Data Factory.
• Strong understanding of Enterprise Data Warehouse, Data Lakehouse, and modern data architecture.
• Experience with REST APIs, CDC, real-time/near-real-time integration, and large-scale data processing.
• Experience working with multiple enterprise source systems and complex data integration requirements.
• Strong production support, troubleshooting, performance tuning, and problem‑solving skills.
• Ability to take end-to-end ownership of enterprise data engineering solutions.

Additional / Advantage Skills

• Power BI Semantic Models, datasets, relationships, DAX, and enterprise BI modelling.
• Azure OpenAI, Azure AI Search, LLM, RAG, embeddings, vector search, semantic search, and AI Agents.
• Experience developing AI-powered chatbots, Data Agents, or enterprise AI applications.
• Git, CI/CD, Azure DevOps, data governance, and data observability.
• Knowledge of modern data architecture and AI-ready data platforms.

Relevant Experience

Experience working in Real Estate, Hospitality & Entertainment is highly valued.