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HT

Senior Data Engineer

Hantec Trader
Posted 6 hours ago
🛂Visa sponsorship
🇦🇪United Arab Emirates
📁Data & Analytics
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Senior Data Engineer

Location: Dubai, UAE


Why Join Hantec Markets?

We’re a global broker with innovation at our core. Designing for us means building tools that empower traders across markets, platforms, and geographies. You’ll be part of a team where ownership is expected, collaboration is celebrated, and creativity is the standard.


About the Role:

We are looking for an experienced Senior Data Engineer with strong expertise in the Microsoft data ecosystem to design, build, and optimize scalable data platforms. You will be responsible for developing modern data pipelines, implementing automation, supporting AI initiatives, and delivering high-quality data solutions that power analytics and business intelligence across the organization.

Important note: As part of the application, candidates are required to provide a summary of the key projects they have worked on, clearly outlining their role, responsibilities, technologies used, and contributions to each project. This will help us better understand their hands-on experience and technical expertise.


Key Responsibilities:

  • Redesign and refactor existing SQL code, data models, and data structures.
  • Build, maintain, and optimize ETL/ELT pipelines using Microsoft Fabric, Azure Data Factory, Azure Synapse Analytics, and Azure Data Lake.
  • Design and implement scalable data warehouse and lakehouse architectures.
  • Develop automated data ingestion, transformation, and orchestration pipelines.
  • Implement data validation, quality checks, monitoring, and automated workflows.
  • Collaborate with Data Analysts to deliver clean, reliable datasets and semantic models for reporting and analytics.
  • Optimize SQL queries, stored procedures, and database performance.
  • Develop and maintain CI/CD deployment processes for data solutions.
  • Drive automation initiatives using Power Automate and other Microsoft automation tools.
  • Support AI and Copilot initiatives by preparing and governing high-quality data for AI-powered solutions.
  • Ensure performance, security, governance, and reliability across all data platforms.
  • Work closely with cross-functional teams to deliver scalable and business-focused data solutions.


Required Skills & Experience:

  • 5+ years of experience as a Data Engineer or Senior Data Engineer.
  • Strong experience with Microsoft Fabric.
  • Hands-on experience with Azure Data Factory, Azure Synapse Analytics, and Azure Data Lake Storage.
  • Extensive SQL Server development experience, including performance tuning and query optimization.
  • Experience designing and maintaining enterprise ETL/ELT pipelines.
  • Strong understanding of data warehouse, lakehouse, and dimensional modeling concepts.
  • Experience with workflow automation using **Power Automate** or similar automation platforms.
  • Exposure to AI, Copilot, or machine learning data integration is highly desirable.
  • Experience with Git, DevOps, and CI/CD pipelines.
  • Knowledge of Power BI semantic models is an advantage.
  • Strong analytical, problem-solving, and communication skills.
  • Ability to work independently while collaborating effectively within a cross-functional team.


Our Values:

  • Own It, Every Time – Responsibility is our standard.
  • Make Things Happen – We act decisively and with purpose.
  • Relationships Matter – We collaborate with intent.
  • Integrity is Everything – No shortcuts. No compromise.


What we offer:

  • Annual Ticket Home - 2,500 AED a year offered after 1 year of employment
  • VISA Sponsorship
  • Health Insurance
  • Annual Discretionary Bonus Pool – rewarding high performance
  • Monthly $100 Core Values Nominations – recognition for living our values
  • Quarterly Core Values Winner – exclusive dinner with our Directors
  • Yearly Core Values Champion – an all-inclusive paid work trip to one of our global offices
  • Work from Other Offices – flexibility to work remotely from our worldwide locations (at employee’s expense)


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