We are seeking an experienced Data Engineer (PySpark) to design, build, optimize, and maintain scalable data pipelines for production environments. The role requires strong hands-on experience in big data processing, pipeline optimization, and deployment using modern data engineering tools and frameworks.
Design, develop, and maintain robust, scalable data pipelines using Python and PySpark
Perform data ingestion, transformation, cleansing, and validation across structured and unstructured datasets
Conduct Exploratory Data Analysis (EDA) to identify data patterns, anomalies, and quality issues
Apply data imputation techniques, data linking, and cleansing to ensure high data quality
Implement feature engineering pipelines to support analytics and downstream use cases
Optimize Spark jobs for performance, scalability, and cost efficiency
Deploy and tune production-grade data pipelines, ensuring reliability and performance
Automate workflows using Apache Airflow and/or Jenkins
Collaborate with cross-functional teams to integrate data solutions into production systems
Write and maintain unit tests to ensure code quality and reliability
Manage source code, CI/CD, and deployments using Git, GitHub, and GitHub Actions
Requirements
Strong proficiency in Python
Extensive hands-on experience with Apache Spark (PySpark)
Experience working with Jupyter Notebooks
Strong knowledge of SQL and NoSQL databases
Proven experience with Git for version control and CI/CD
Hands-on experience with Apache Airflow and/or Jenkins for scheduling and automation
Solid understanding of data engineering best practices in production environments
Demonstrated experience in Spark performance tuning and optimization
Ability to write clean, testable, and maintainable Python code
Previous production experience is a MUST, specifically in deploying, tuning, and maintaining data pipelines in production environments
Experience working in high-volume or big data environments
Strong problem-solving and analytical skills
Ability to work independently in a fast-paced environment
Competitive salary package
Opportunity to work on production-scale data platforms
Exposure to modern data engineering tools and practices
Dubai-based role with a dynamic and collaborative work environment
Skills Required
- Strong proficiency in Python
- Extensive hands-on experience with Apache Spark (PySpark)
- Experience working with Jupyter Notebooks
- Strong knowledge of SQL and NoSQL databases
- Proven experience with Git for version control and CI/CD
- Hands-on experience with Apache Airflow and/or Jenkins for scheduling and automation
- Experience managing source code, CI/CD, and deployments using Git, GitHub, and GitHub Actions
- Solid understanding of data engineering best practices in production environments
- Demonstrated experience in Spark performance tuning and optimization
- Ability to write clean, testable, and maintainable Python code and unit tests
- Previous production experience deploying, tuning, and maintaining data pipelines in production environments
- Experience working in high-volume or big data environments
- Strong problem-solving and analytical skills
- Ability to work independently in a fast-paced environment
What We Do
Black Pearl is a leading HR consultancy and specialist recruitment firm based in the UAE and GCC. They provide customized HR solutions, executive search, and strategic recruitment services across various corporate support, finance, accounting, and business operations roles, helping clients achieve success through tailored staffing and HR consulting services.
