Lead Data Engineer (AWS Data Platform)

Lead Data Engineer (AWS Data Platform)

Position: Lead Data Engineer (AWS Data Platform) Experience: 5 to 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 Lead Data Engineer with 5 to 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 to 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.