Senior Data Engineer - Databricks & Cloud Data Lakes

Flentas Technologies; Dubai; On-site; AED 250,000 - 400,000; Full time

Job summary

Flentas Technologies in Dubai (UAE) is seeking a Data Engineer with 7-10 years of experience to design and optimize scalable data platforms and pipelines. You will work with Python, PySpark, Databricks, AWS, SQL, and modern data engineering practices to deliver enterprise-grade solutions.

You will build batch and real-time data pipelines, create data lakes/lakehouse and data warehouses, and collaborate with data scientists and stakeholders to translate requirements into robust data solutions.

Qualifications

• 7–10 years of Data Engineering, Big Data, or Cloud Data Platforms experience.
• Strong Python, PySpark, Databricks, AWS Cloud, and SQL skills.
• Experience building scalable ETL/ELT pipelines and data warehousing concepts.
• Familiarity with Airflow or similar orchestration tools.

Responsibilities

• Design, develop, and maintain scalable batch and real-time data pipelines.
• Build ingestion frameworks for structured, semi-structured, and unstructured data.
• Develop and optimize data transformation workflows with Python, PySpark, and Databricks.
• Implement ETL/ELT processes for large-scale analytics and reporting.
• Design and maintain Data Lakes, Lakehouse architectures, and Data Warehouses.
• Collaborate with Data Scientists and Stakeholders to translate requirements.
• Ensure data quality, integrity, security, and governance across platforms.
• Optimize Spark jobs, SQL queries, and cloud resources for performance and cost.
• Implement monitoring, logging, and alerting for data pipelines.
• Contribute to architecture discussions and code reviews.

Skills

Python

PySpark

Databricks

SQL

AWS Cloud

Data Engineering

Spark

Git

Tools

Airflow

Delta Lake

Lakehouse

Job description

Flentas Technologies in Dubai (UAE) is seeking a Data Engineer with 7-10 years of experience to design and optimize scalable data platforms and pipelines. You will work with Python, PySpark, Databricks, AWS, SQL, and modern data engineering practices to deliver enterprise-grade solutions.

You will build batch and real-time data pipelines, create data lakes/lakehouse and data warehouses, and collaborate with data scientists and stakeholders to translate requirements into robust data solutions.