Senior Data Engineer

Position: Senior Data Engineer Experience: 5–8 Years Location: Hybrid (Pakistan)

Note: (Candidates must be available during UAE business hours and follow UAE public holidays)

Job Summary

We are seeking a highly skilled Senior Data Engineer with 5–8 years of experience in designing, developing, and optimizing large-scale data platforms and ETL/ELT pipelines. The ideal candidate will have strong hands-on expertise in PySpark, AWS Glue, Amazon EMR, Amazon Redshift, and SQL-based data warehousing , along with proven experience in performance tuning and data optimization.

The candidate will work closely with a UAE-based customer and must be comfortable collaborating with distributed teams while adhering to UAE working hours and holiday schedules.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using PySpark , AWS Glue , and Amazon EMR .
• Build and optimize data ingestion, transformation, and processing frameworks for structured and semi-structured data.
• Develop and maintain enterprise data warehouse solutions using Amazon Redshift .
• Write complex SQL queries, stored procedures, and data transformations to support analytics and reporting requirements.
• Implement ETL/ELT processes to move data efficiently across multiple systems and platforms.
• Perform performance tuning and optimization of Spark jobs, ETL pipelines, SQL queries, and Redshift workloads.
• Ensure data quality, integrity, security, and governance across data platforms.
• Troubleshoot production issues and perform root cause analysis for data-related incidents.
• Collaborate with business stakeholders, analysts, architects, and engineering teams to understand data requirements.
• Participate in code reviews, technical design discussions, and best-practice implementation.
• Monitor data pipelines and proactively identify opportunities for performance improvements and automation.
• Create and maintain technical documentation, data models, and operational procedures.

Required Skills & Experience

Must-Have Skills

• 5–8 years of experience in Data Engineering and Data Warehousing.
• Strong hands-on experience with PySpark .
• Extensive experience with AWS Glue .
• Experience building and managing workloads on Amazon EMR .
• Strong expertise in Amazon Redshift .
• Excellent SQL development and query optimization skills.
• Strong understanding of Data Warehousing concepts, dimensional modeling, and ETL/ELT processes.
• Experience in performance tuning of Spark jobs, SQL queries, ETL pipelines, and data warehouse workloads.
• Experience handling large-scale datasets and distributed data processing.
• Strong debugging, troubleshooting, and analytical skills.

Preferred Skills

• Experience with additional AWS services such as S3, IAM, CloudWatch, Lambda, and Step Functions.
• Knowledge of CI/CD pipelines and DevOps practices for data platforms.
• Experience with workflow orchestration tools.
• Familiarity with data governance, security, and compliance practices.
• Exposure to Agile/Scrum development methodologies.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related field.
• Relevant AWS certifications will be considered an advantage.

Soft Skills

• Strong communication and stakeholder management skills.
• Ability to work independently in a remote environment.
• Excellent problem-solving and analytical thinking abilities.
• Ability to collaborate effectively with cross-functional and geographically distributed teams.
• Strong ownership mindset and commitment to delivering high-quality solutions.