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.